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Open Access Article
1 - Using the new meta-heuristic algorithm to determine the optimal capacity and location of electric car parking with the presence of renewable energy sources in the distribution system
Reza SedaghatiDue to the importance of distribution systems, optimal planning and safety of these networks are very important. On the other hand, electric vehicles are one of the main characteristics of future electricity distribution networks. The uncoordinated and unmanaged presenc MoreDue to the importance of distribution systems, optimal planning and safety of these networks are very important. On the other hand, electric vehicles are one of the main characteristics of future electricity distribution networks. The uncoordinated and unmanaged presence of electric vehicles as an additional load in the network can aggravate problems such as voltage drop, voltage stability and increase in network losses. In order to alleviate the effects caused by the uncontrolled presence of these cars, it is necessary to manage their required power in coordination with other dispersed production sources. Therefore, we should try to reduce losses by properly planning the charging and discharging of cars, along with scattered productions, having the right voltage and, as a result, better economic efficiency. Therefore, in this article, the optimal use of electric car parking lots with the presence of renewable energy sources in the distribution system has been studied. Optimization of the problem, a new meta-heuristic algorithm based on the flower pollination algorithm was used to determine the variables of the problem, including the optimal capacity and location of solar sources, as well as electric parking lots and diesel generators in the distribution network. The problem is subject to network operation restrictions (thermal line restrictions, network bus voltage restrictions, etc.), the number of cars in electric parking lots, the permitted power capacity of solar units, and the capacity of diesels have been optimized. In this study, the capability of the proposed method based on the flower pollination algorithm has been evaluated with other algorithms. The simulation was done on the distribution network of 33 IEEE buses, and the results show that the convergence speed and accuracy of the proposed method is high. Manuscript profile -
Open Access Article
2 - Assessing energy performance of simulation-powered internal sun shading devices for residential buildings in Tehran
Alireza Karimpour darab diba Iraj EtesamSustainable development as a process for meeting human development goals while sustaining the ability of natural systems to continue to provide the natural resources has an undeniable impact on all aspects of human life. Energy efficiency is an essential factor for sust MoreSustainable development as a process for meeting human development goals while sustaining the ability of natural systems to continue to provide the natural resources has an undeniable impact on all aspects of human life. Energy efficiency is an essential factor for sustainable development and in spite of worldwide climate change problems caused by fossil fuel use, energy consumption levels in Iran, while already high, continues to rise each year. About 40% of energy consumed by the residential buildings in this country is fossil fuel-derived. Therefore providing solutions to reduce energy consumption in this sector is very important. Tehran is largest city of Iran, and significant amounts of energy are consumed in these city. However, due to its location in semi-arid climatic region, high sun’s radiation even in winter and low relative humidity of the air, this city has a high potential for energy conservation in residential buildings. Therefore the introduction of energy efficient buildings in this city would have a significant overall impact on national energy consumption levels. Sun shading devices are one of the most efficient elements to manage the interaction between the interiors and exteriors of buildings. They can significantly reduce cooling loads, improve thermal comfort, prevent the heat loss in the winter and reduce potential glare problems in residential buildings. Sun shading devices can be categorized according to their placement as interior, exterior and mid-pane. Result of research and studies shows that the effectiveness increase 35% by using outside shade protection instead of inside one. This research is aware of this fact that optimized internal sun shading devices are not comparable with the external sun shading devices in efficiency and performance. Although due to the increased utilization of them in the residential buildings, this research studied the internal sun shading devices and determined the optimized internal sun shading system, and then analyzed its effect on the energy consumption in the residential building model. In this study at the first phase, the combination of four types of internal sun shading devices with three types of windows are evaluated by the Parasol simulation software to determine the optimized internal sun shading system. Simulations show that the double glazed transparent window with dense reflective Roller Blind (as optimized sun shading system), has most appropriate thermal behavior. At the next step, a building model as a case study (The six-story apartment in the city of Tehran) was considered for simulations of energy consumption. The Building Calc. software was applied for energy simulations and heating, cooling and total energy consumption of building was calculated with and without optimized internal sun shading system. The result shows that efficiency of internal sun shading devices increase by using dense texture, high reflectance and low transfer rate. Also only by using optimized internal sun shading system reduce energy consumption of residential buildings in Tehran up to 14%. Because of the large coordination with Iran’s economic, cultural and social conditions this method could be one of the best solutions to reduce the energy demand in residential buildings. Manuscript profile -
Open Access Article
3 - Sustainable Prefabricated Structure Design by Salt Sediment Inspired from Material Distribution Optimization of Human Trabecular Bone
Azin Jalali mahmoud golabchiNature can be an interesting source of human inspiration for design and inventions. Man has been always related to the nature in different levels. Bionic Architecture is a new trend in contemporary world that benefits from sustainable nature`s solutions for human proble MoreNature can be an interesting source of human inspiration for design and inventions. Man has been always related to the nature in different levels. Bionic Architecture is a new trend in contemporary world that benefits from sustainable nature`s solutions for human problems. There are two main methods of bio inspired design, First: Bottom-Up or solution based method, Second: Top-Down or problem based method. The authors used Top-Down or problem based method to find the article`s main question: How to design a sustainable self-growing and self-compacting structure which is cheap and uses minimum material. First there was problem of construction with minimum material usage and ecosystem damage, then human bone as an inspiring source was focused on, and abstracted form modeled by 3D printers can lead this basic prototype to industrial mass production. This article aims to find a solution for problem of over extracting materials from environment which is a factor of unsustainability in architecture and construction industry. It tries to discover the pattern of how structures optimize their material usage to build their selves. Natural structures extract needed materials from their context gradually, an example of these structures in nature is human bone that have balance between strength, weigh and material distribution. How to simulate this semi prefabricated, self-compacting and intelligent structure able to self-healing and self-destroying itself in essential parts and gradually extract material from its context environment grows and completes itself is the result of this article. The process of simulation from natural model to industrial sample is discussed in the main text. The process contains these steps: Discovering bone structure, Abstracting bone pattern, Simulating bone growth, and providing sediment phase. Bone structure can be simulated into two different ways. One of them is using random points as basic matrix and the other one is Voronoi pattern. Both of these methods can be modeled by Grasshopper plugin and Rhino software. After modeling abstracted Trabecular pattern as basic matrix, it can be made by 3D printers which use cheap and abundant material like sand. The basic sand matrix is put into over salinized water to become more and more compacted by time duration and salt sediments. The Piezoelectric property of the bone cells could be ignited by external forces is the basic cause of calcium ions absorption from bloodstream and calcium precipitation on bone matrix. Bone grows up according to the direction of the external force vectors. Simulation of this dynamic process in a smart structure that builds and destroys and repairs itself is proposed to use Quarts sensors which has the same piezoelectric feature and can simulate the behavior of bone calcium precipitation by making heat from the forces that have to bear and making heat as reaction. The material for process of structure growth is salt (sea salt). As the water of Persian Gulf or Lake Urmia is facing over salinization crisis, extracting salt from these over salty water and returning less salty water to its source can supply environmental sustainability of this kind of construction method. Manuscript profile -
Open Access Article
4 - Synthesis, Optimization and Modeling of Curdlan Gum Production from Paenibacillus polymyxaUsing Response Surface Methodology (RSM)
S.M. Rafigh M. Vossoughi A. Vaziri A.A. Safekordi M. ArdjomandIntroduction: Curdlan gum is a bacterial polysaccharidic biopolymer that is the result of β-(1→3)-D-glycosidic linkages. Due to its ability to curdle and the water-holding capacity, curdlan has applications in the manufacture of food products such as jelly, no MoreIntroduction: Curdlan gum is a bacterial polysaccharidic biopolymer that is the result of β-(1→3)-D-glycosidic linkages. Due to its ability to curdle and the water-holding capacity, curdlan has applications in the manufacture of food products such as jelly, noodles, edible fibers. Curdlan is biodegradable, nontoxic and it has applications in the pharmaceutical industry because of its potent biological activities. For the first time, the present study is concerned with the synthesis, characterization, optimization of cultural conditions and modeling of curdlan production from Paenibacillus polymyxa using RSM. Materials and Methods: After preparation of the microorganism and the medium, Plackett–Burman design with 12 experimental runs was used to screen the effective factors through 11 variables of batch culture medium for curdlan production. Central composite design with 20 experimental runs was used for optimization of the effective variables. In addition, four characterization methods such as FT-IR, C-NMR, XRD and DSC were employed. Results: The result of the experiments showed that three nutritional factors (glucose, yeast extract and triton x-100) had the predominant effect on curdlan production. The maximum production of curdlan was 4.75 g/l from the optimum condition consisting of glucose (100 g/l), yeast extract (3 g/l) and triton x-100(2.5 g/l). In addition, the average molecular weight of curdlan was determined at 170 kDa by GPC. Conclusion: The results from this study have demonstrated that Paenibacillus polymyxa PTCC 1020 with more specific growth rate (µ) than previous studies is capable to produce curdlan gum and also the production of the synthetic curdlan was confirmed using qualitative methods of identification. Manuscript profile -
Open Access Article
5 - Parameter setting of technical analysis indicators using multi-objective particle swarm optimization and adaptive fuzzy inference system
Ibrahim Abbasi Hossein Akefi Shahaboddin AdibmehrIn this paper, we propose automatic stock trading system which combines technical analysis and adaptive neural fuzzy inference system to predict the stock price trend to increase return of investment. In this trading system, at first the optimal value of technical indic MoreIn this paper, we propose automatic stock trading system which combines technical analysis and adaptive neural fuzzy inference system to predict the stock price trend to increase return of investment. In this trading system, at first the optimal value of technical indicator's parameters is determined by using multi-objective particle swarm optimization and according to these parameters; technical indicators are calculated to predict stock price changes with the help of adaptive neural fuzzy inference system. We have chosen eight different stocks from Tehran stock exchange to test our trading system for two months. A computational experience is carried out in order to analyze the proposed algorithm and the obtained results are compared with usual conventional methods which have been proposed in previous researches. The computational results show our proposed method performs better than other previous methods and obtains superior results. Manuscript profile -
Open Access Article
6 - انتخاب رهبران رای با استفاده از الگوریتم بهینه سازی گرگ خاکستری در شبکه های اجتماعی
صمد محمد اقدم فرهاد سلیمانیان قره چپق محمد مصدریسرویس های شبکه های اجتماعی دیجیتال همان شبکه های اجتماعی هستند که مردم به اصطلاح عامیانه از این واژه استفاده می کنند. پلتفرم های رسانه های اجتماعی و وب سایت هایی که انتقال دانش از طریق شبکه های اجتماعی را امکان پذیر می کنند، ابزارهای دیجیتالی هستند که برای ساخت شبکه های Moreسرویس های شبکه های اجتماعی دیجیتال همان شبکه های اجتماعی هستند که مردم به اصطلاح عامیانه از این واژه استفاده می کنند. پلتفرم های رسانه های اجتماعی و وب سایت هایی که انتقال دانش از طریق شبکه های اجتماعی را امکان پذیر می کنند، ابزارهای دیجیتالی هستند که برای ساخت شبکه های اجتماعی و توسعه آنها طراحی شده اند. علاقه و استفاده زیاد از شبکه های اجتماعی این محیط ها را برای فعالیت های مختلف از جمله اقتصادی، فرهنگی، سیاسی و ... مهیا کرده است. رهبران رای یکی از مهمترین مواردی هستند که در این محیط ها تأثیر زیادی بر سایر کاربران دارند. رهبران رای در شبکه های اجتماعی سودمند هستند و ما می توانیم با شناسایی آنها از توانمندی و نفوذ آنها استفاده کنیم. در این مقاله، ما رهبران رای را با استفاده از الگوریتم بهینه سازی گرگ خاکستری انتخاب کرده ایم. این روش سلسله مراتب رهبری و سازوکار شکار گرگهای خاکستری را در طبیعت تقلید می کند و شامل 3 مرحله اصلی شکاریعنی جستجوی طعمه، محاصره طعمه و حمله به طعمه است. بر اساس بررسی ها و نتایج حاصله، تعداد رهبران واقعی رای تشخیص داده شده توسط این الگوریتم قابل توجه است و مزیت روش پیشنهادی سازگاری با معیارهای مختلف و ارائه نتایج پایداری درروش های مختلف است. Manuscript profile -
Open Access Article
7 - Design of Optimal Sugeno-type fuzzy Controller for Speed Control of DC Motor Including Drive and Chopper Dynamic Considering Multi-Objective Optimization Using Teaching Learning Optimization Algorithm
ali sedaratnia majid moradi zirkohi najmeh cheraghi shiraziDue to the simple structure of DC motors, these motors have found many applications in industry.Therefore, in this paper, the speed control of DC motor is investigated by considering the dynamics of drive and chopper with Sugeno-type fuzzy controller. A chopper is used MoreDue to the simple structure of DC motors, these motors have found many applications in industry.Therefore, in this paper, the speed control of DC motor is investigated by considering the dynamics of drive and chopper with Sugeno-type fuzzy controller. A chopper is used to control the voltage applied to the DC motor armature. Considering the dynamics of the chopper drive increases the complexity of the system. After designing the fuzzy controller to increase the performance of the control system, the fuzzy controller parameters are adjusted using a teaching-learning-based optimization algorithm. This algorithm is new and one of its features is its small number of parameters. The results show that the fuzzy controller has better performance against changes in system parameters and uncertainties compared to the classic PID controller. Considering the appropriate criterion function, the value of the cost function for the proposed method is 0.2. But with the optimized PID controller about 0.31 which shows a 55% superiority of the proposed method. Manuscript profile -
Open Access Article
8 - Design of Anomaly Based Intrusion Detection System Using Support Vector Machine and Grasshopper Optimization Algorithm in IoT
Sepehr Sharifi Soulmaz GheisariComputer networks play an important and practical role in communication and data exchange, and they also share resources with complete ease. Today, various types of computer networks have emerged, one of which is the Internet of Things. In the Internet of Things, networ MoreComputer networks play an important and practical role in communication and data exchange, and they also share resources with complete ease. Today, various types of computer networks have emerged, one of which is the Internet of Things. In the Internet of Things, network nodes can be smart objects, and in this sense, this network has many nodes and there is a lot of traffic in this network. Like any computer network, it faces its own challenges and problems, one of which is the issue of network intrusion and disruption. This dissertation focuses on detecting anomaly-based intrusion into the Internet of Things using data mining. In this study, after collecting and preparing data, the improved support vector machine with grasshopper optimization algorithm is used as a proposed method to detect anomaly-based intrusion in the Internet of Things. The bagging and k-nearest neighbor classifiers and Basic SVM are compared based on error types and standard performance criteria. The simulation results show 97.2% accuracy in the proposed method and better performance compared to other methods. Manuscript profile -
Open Access Article
9 - Reduce spike noise from artificial aperture radar (SAR) images using Corvette conversion
Ameneh Rajabpour boshehri Ahmad KeshavarzIn this paper, an adaptive method based on carroll conversion is introduced to reduce spike noise. Speckle noise is a multiplicative impurity that in this paper we first convert to mass with a preprocessing step. An interest function is then introduced to threshold the MoreIn this paper, an adaptive method based on carroll conversion is introduced to reduce spike noise. Speckle noise is a multiplicative impurity that in this paper we first convert to mass with a preprocessing step. An interest function is then introduced to threshold the Coralt coefficients, which has three general thresholds. An objective function, based on an estimated noise correlation with the edges of the output image, then provides the optimal parameters in the threshold of the interest function by searching with a general search algorithm called the particle swarm optimization algorithm. The appropriate objective function is then considered for the PSO algorithm search and the results of speckle reduction are measured by the Violet method. Manuscript profile -
Open Access Article
10 - Introducing a new query database optimization method
Peyman Arebi Amir Masoud Bidgoli Serajodin KatebiThe grid database tries to store and scatter data over a wide geographical area in order to create a structure for storing data across the lattice environment in a distributed and heterogeneous manner. Due to the large amount of data, transaction processing in such an e MoreThe grid database tries to store and scatter data over a wide geographical area in order to create a structure for storing data across the lattice environment in a distributed and heterogeneous manner. Due to the large amount of data, transaction processing in such an environment is very complex and time consuming. Obviously, using queries without optimization will greatly reduce the efficiency of transactions in this database, while using appropriate optimization algorithms can greatly increase efficiency. Many algorithms have been proposed to optimize queries, but due to the different network environments, different optimization algorithms are needed. This paper presents an algorithm that is consistent with the structure of lattice computing and works well in lattice database systems with high data volumes. Manuscript profile -
Open Access Article
11 - Improving the Stability of a Power System Including SVC Based on Energy Function Minimization in a Multi-Model Optimal Coordinated Control Structure
Elaheh Pagard Shahrokh Shojaeian Mohammad Mahdi RezaeiIn this paper, the improvement of low frequency oscillation (LFO) damping in a power system including SVC is investigated. To achieve this goal, a new control strategy has been presented in which the multi-model controller is optimized using the linear optimal controlle MoreIn this paper, the improvement of low frequency oscillation (LFO) damping in a power system including SVC is investigated. To achieve this goal, a new control strategy has been presented in which the multi-model controller is optimized using the linear optimal controller (LOC) and the particle swarm algorithm (PSO). The control bank in the multi-model controller includes three LOC controllers that generate optimal signals through the linearization of the nonlinear equations of the system and the minimization of an energy function to be combined by the Bayes recursive algorithm simultaneously to the generator excitation system and SVC. In order to generate an optimal linear signal, Riccati's equation must be solved; Riccati's equation includes two weight matrices Rric and Qric. These matrices elements are optimized by PSO algorithm. The PSO algorithm has calculated the optimal Rric and Qric with two different objective functions of maximizing the eigenvalues and minimizing the area under the speed curve. To evaluate the MMC-LOC-PSO control strategy, the symmetrical three-phase error is applied to the worst bus and the results of these two objective functions are compared. The simulation of the single machine power system has been done by MATLAB. The proposed control strategy, while maintaining stability, also effectively damps the LFOs, in addition, the permanent rotor speed and rotor angle error have also been favorably pushed to zero. Manuscript profile -
Open Access Article
12 - Stable Feature Selection and Clustering According to Hierarchical Structures Based on Chaotic Multispecies Particle Swarm Optimization Applied for Genetic Data Diagnosis and Prognosis
Maryam yassi Mohammad Hossein Moattarb Mehdi YaghoobiAny abnormal reproduction of cells is a tumor. censer happens when there’s an unstrained growth of abnormal cells. Cancer and tumors are divided in to two types, malignant and benign. Given the growth in the environmental information, it’s essential to emplo MoreAny abnormal reproduction of cells is a tumor. censer happens when there’s an unstrained growth of abnormal cells. Cancer and tumors are divided in to two types, malignant and benign. Given the growth in the environmental information, it’s essential to employ some tools to analyze this data and gain the knowledge embedded in it. Since large-scale problems and huge data bases are incomprehensible for the human, employing intelligent methods is effective in understanding large-scale data better. In this paper, the integration methods are a subset of rating measures each with a specific objective of sustainable features for superior selection of distinct features.The next step would discuss creating a fuzzy system (FS) to detect and classify between benign and malignant nature of biological data. Fuzzy system type is Takagi-Sugeno-Kang (TSK). To classify a hierarchical structure of multi-species particle swarm algorithm based on chaotic particle can be used to optimize the fuzzy system. In addition, using chaotic theory discerns the true diversity of the particles and increases the power to detect and classify the samples. Accurate identification and classification of malignant and benign biological nature of the data is more than 95%. This simulation is performed on UCI and Microarray data-base. Manuscript profile -
Open Access Article
13 - شناسایی سیستمهای فوق آشوب با استفاده از مدل شبکه عصبی ELM و بهبود تخمین پارامترهای آن با استفاده از الگوریتم فرااکتشافی جستجوی فرکتالی تصادفی بهبود یافته
محدثه شکراللهی مهدی یعقوبی -
Open Access Article
14 - سیستم پیشنهاددهنده ترکیبی، تابع فراموشی، آنتولوژی، رابطه ی
negin Misagheian Mehrdad Jalali Saeed Sanoobariاخیراً سیستم های برچسب زنی مردمی به صورت روزافزون در حال افزایش یافتن و متداول شدن می باشد . این سیستم ها به کاربران اجازه میدهند منابع مورد نیاز خود را به صورت آزادانه سازماندهی، مدیریت و جستجو نمایند . از چالش های این نوع سیستمها میتوان به حجم بالای داده، دادههای نا Moreاخیراً سیستم های برچسب زنی مردمی به صورت روزافزون در حال افزایش یافتن و متداول شدن می باشد . این سیستم ها به کاربران اجازه میدهند منابع مورد نیاز خود را به صورت آزادانه سازماندهی، مدیریت و جستجو نمایند . از چالش های این نوع سیستمها میتوان به حجم بالای داده، دادههای ناسازگار، استفاده از الگوریتم های زمان بر یادگیری ماشین، زمان طولانی برای ارائه پیشنهاد به کاربر، صحت پایین در ارائه پیشنهادات و عدم قابلیت اجرا در دنیای واقعی اشاره نمود . این چالش ها سبب افزایش روزافزون تحقیقات در سالهای اخیر شده است. در این مقاله سیستم پیشنهاد دهندة ترکیبی منبعی معرفی نمودهایم که با به کارگیری اطلاعات مهم موجود در سیستمهای برچسبزنی مانند زمان و همچنین آنتولوژی موجود، صحت نتایج پیشنهادی را بهبود داده است. Manuscript profile -
Open Access Article
15 - Increasing the efficiency of solar trackers by honey bee optimization algorithm
Hadieh Sadat Hosseini Amangaldi Koochaki Masood RadmehrMost of Control systems that often used in solar trackers, use signals from the solar radiation sensorwere placed on photovoltaic panels and control mutation of panel’s motors. Since, Sun information islimited and real time measurement is difficult, the solar trac MoreMost of Control systems that often used in solar trackers, use signals from the solar radiation sensorwere placed on photovoltaic panels and control mutation of panel’s motors. Since, Sun information islimited and real time measurement is difficult, the solar tracking algorithms developed withoutadditional hardware and sensors. This paper presents a method for determining the tilt and azimuthangle trajectories based on Bee Optimization Algorithm for PVs in order to achieve maximum outputenergy. Open-loop two axis sun tracking system is considered. The results show an increasing inenergy obtained by BA compared with Differential Evolution algorithm. Manuscript profile -
Open Access Article
16 - Agility Agents In Supply Chain of Educational Organizations Using Particle Swarm Optimization Algorithm
Abbass Toloie Ashlaghi shahrzad tayaran Reza Radfar Alireza PourebrahimiThe increasing speed of technological change, on the one hand, and the changing nature of customer demand and the intensification of competition among organizations, on the other hand, have led organizations to seek to take on new competitive advantages to outperform co MoreThe increasing speed of technological change, on the one hand, and the changing nature of customer demand and the intensification of competition among organizations, on the other hand, have led organizations to seek to take on new competitive advantages to outperform competitors and better meet customer needs. Achieving such goals comes in the context of a new concept called "organizational agility," but agility of the organization is influenced by its agents, which are the most influential factor in service companies. In this research, which the University of Science and Research has proposed as a case study, the employees are divided into three categories: Soft, Grievous, and Blind. These factors determine the three main elements of the agility of the supply chain organization: Agility drivers, agility abilities and agility capability. Also, using a particle swarm optimization algorithm, an intelligent model has been designed to measure the impact and impact of factors on each other. And after implementing the model in a case study at Time = 769, recovery is at best possible. Manuscript profile -
Open Access Article
17 - Solving Resource-Constrained Project Scheduling Problem with Particle Swarm Optimization (Case Study: Bandar Abbas Gas Condensate Refinery)
Mohammadhusein Nabizadeh Huseinali Hasanpoor Roozbeh Azizmohammadi Navid HashtroodiOne of the issues considered by the projects responsible especially project managers is the execution of project activities according to time schedule. The very difficult nature of that issue is also another reason for the researchers to take much note of it. Therefore, MoreOne of the issues considered by the projects responsible especially project managers is the execution of project activities according to time schedule. The very difficult nature of that issue is also another reason for the researchers to take much note of it. Therefore, there are especial techniques and methods to solve those issues. Also, project managers pay much attention to the stability of the time schedule as it is important for them. This paper is provided with a real project time schedule for a refinery by using stable time schedule. Particle swarm optimization algorithm is suggested to resolve the problem since the project time schedule has resources limitation including NP- Hard. In order to accesses the validation of the model, 4 issues with small scales has been selected and the results from the suggested algorithm was compared with the accurate result obtained from lingo software. These results indicate that the suggested algorithm is effective and convergent with the optimized result. Manuscript profile -
Open Access Article
18 - Particle swarm optimization in optimal control problems for Car on a constrained piecewise affine hill
Ahmad Kia Kojouri Javad MashayekhiFardIn spite of all the Demonstrate Prescient Control (MPC) based arrangement preferences such as ensuring soundness, the most impediment such as an exponential development of the number of the polyhedral locale by expanding the expectation skyline exists. This causes an in MoreIn spite of all the Demonstrate Prescient Control (MPC) based arrangement preferences such as ensuring soundness, the most impediment such as an exponential development of the number of the polyhedral locale by expanding the expectation skyline exists. This causes an increase in the computation complexity of control law. In this paper, we consider the arrangement to ideal control issues for constrained piecewise affine systems based on demonstrating predictive control. After that, we utilize particle swarm optimization calculation to complexity diminishment of arrangement and alter the framework execution. In truth the point of the paper is twofold. To begin with, we consider the hypothetical comes about on the structure of the control law. At the minute, we portray how the complexity of deciding control law can be capable of decreased and moving forward system execution at the same time by utilizing particle swarm optimization. The considered calculation is associated with a Car on a constrained piecewise affine hill and the result is shown to the advantage of our analysis. The objective of the car is to climb to the top of a steep slope and then preserve its position at the top (the beginning), without falling from the piecewise affine environment. The number of control law polyhedrals diminishes from 129 to 25. Manuscript profile -
Open Access Article
19 - Artificial Neural Networks Models for Rate of Penetration Prediction in Rock Drilling
Naser Ebadati‎ Mehrab ‎ AziziBased on field data, there are various methods to reduce the cost of drilling wells. One of these methods is to optimize the drilling parameters to obtain the maximum rate of penetration (ROP). Many parameters affect ROP. The main purpose of this research is the use of MoreBased on field data, there are various methods to reduce the cost of drilling wells. One of these methods is to optimize the drilling parameters to obtain the maximum rate of penetration (ROP). Many parameters affect ROP. The main purpose of this research is the use of smart networks for the penetration rate of drilling, for this purpose, well input data including drilling depth, duration of the drilling operation, speed of rotation of the drill, weight on the drill, weight and volume of drilling mud as input data. And the drilling penetration rate was prepared as output data from one of the fields located in the Persian Gulf. 70% of data is allocated for network training, 15% of data for validation and 15% of data for sensitivity analysis. According to the obtained results, it was found that using this tool, a good relationship with the total regression coefficient (0.96) is obtained for predicting the penetration rate using a neural network. Also, by repeating the calculations in repetition 12, the best value was obtained, which is equal to 14.24. Manuscript profile -
Open Access Article
20 - Artificial Neural Networks Models for Rate of Penetration Prediction in Rock Drilling
naser ebadati Ronak Parvaneh Mehrab AziziBased on field data, there are various methods to reduce the cost of drilling wells. One of these methods is to optimize the drilling parameters to obtain the maximum rate of penetration (ROP). Many parameters affect ROP. The main purpose of this research is the use of MoreBased on field data, there are various methods to reduce the cost of drilling wells. One of these methods is to optimize the drilling parameters to obtain the maximum rate of penetration (ROP). Many parameters affect ROP. The main purpose of this research is the use of smart networks for the penetration rate of drilling, for this purpose, well input data including drilling depth, duration of the drilling operation, speed of rotation of the drill, weight on the drill, weight and volume of drilling mud as input data. And the drilling penetration rate was prepared as output data from one of the fields located in the Persian Gulf. 70% of data is allocated for network training, 15% of data for validation and 15% of data for sensitivity analysis. According to the obtained results, it was found that using this tool, a good relationship with the total regression coefficient (0.96) is obtained for predicting the penetration rate using a neural network. Also, by repeating the calculations in repetition 12, the best value was obtained, which is equal to 14.24 Manuscript profile -
Open Access Article
21 - The effect of the type of objective function to detect damage on the cracked beam clamped to multi-objective optimization methods
javad kheyroddin ehsan jamshidi alireza arghavanOne of the most important issues that is widely industry, monitoring the situation. To work with this system defects before he could create serious problem and known to tackle it. Damage in two ways: existent malicious and nondestructive and from where the solution with MoreOne of the most important issues that is widely industry, monitoring the situation. To work with this system defects before he could create serious problem and known to tackle it. Damage in two ways: existent malicious and nondestructive and from where the solution with less cost, so this method is more. One of the methods of identifying damage nondestructive ,methodology Modal parameters structure in this way is to investigate the changes Modal parameters, such as the natural frequencies and modes form before and after the damage to seek the site and levels of damage in are structures and damage to find with a wide range of response so a lot of research hit optimization techniques used in solving the problem for considering the dynamic parameters and changes in the structure that objective functions is considered to be optimized for them , and the amount of damage to the desired effectively The study by using the method of genetic algorithm to examine the structural damage, with regard to the presence of various target functions, first as a single point, and the accuracy of the response to the parameters for change in the algorithm sensitivity analysis, and then paid using various target functions and optimized genetic algorithm multi-purpose of the appropriate response is obtained. Manuscript profile -
Open Access Article
22 - Clearance Prediction of Rotary System with and without Mechanical Diagnosis by Using Artificial Neural Networks and Particle Swarm Optimization
Mojtaba Hasanluلقی تکیه گاه های موتور و یاتاقان ها سیستم را با کوپلینگ 4 نوع مختلف عیب ابتدا با استفاده از روش تبدیل سریع فوریه فرکانس ها و جابجایی های عمودی شفت در محل دو یاتاقان استخراج نموده و سپس اثر لقی تکیه گاه ها را در حالت حضور و عدم حضور عیوب دیگر مورد بررسی قرار میگیرد. حال Moreلقی تکیه گاه های موتور و یاتاقان ها سیستم را با کوپلینگ 4 نوع مختلف عیب ابتدا با استفاده از روش تبدیل سریع فوریه فرکانس ها و جابجایی های عمودی شفت در محل دو یاتاقان استخراج نموده و سپس اثر لقی تکیه گاه ها را در حالت حضور و عدم حضور عیوب دیگر مورد بررسی قرار میگیرد. حال برای دستیابی به یک مدل بهینه از شبکه عصبی بهمراه الگوریتم بهینه سازی ازدحام ذرات تک هدفه استفاده می کنیم بدین صورت که یکبار فرکانس های سیستم معیوب و بدون بعنوان ورودی شبکه عصبی معرفی میگردند و خروجی مطلوب آن فرکانس سیستم در حالتی که سیستم هیچ گونه عیبی ندارد مدلسازی می شود و سپس در مرحله بعد فرآیند قبل جهت مدل سازی بیهنه با شبکه عصبی را با استفاده از جابجایی های معیوب(وروی شبکه عصبی) و جابجایی سیستم (ورودی مطلوب) مورد ارزیابی قرار میگیرد. Manuscript profile -
Open Access Article
23 - The Impact of Employability on Career Success of Employees at Qazvin Product Distribution Company
Seyyed Mohammad Zahedi Soheila ZakizadehPresent research addresses the impact of employability on career success of employees of Qazvin Province National Oil Product Distribution Company. Statistical population of present research consisted of 203 employees of Qazvin Province National Oil Product Distribution MorePresent research addresses the impact of employability on career success of employees of Qazvin Province National Oil Product Distribution Company. Statistical population of present research consisted of 203 employees of Qazvin Province National Oil Product Distribution Company. 190 subjects were selected, using simple random sampling. The first research instrument was van der Heijden and van der Heijden’s Employability scale with five dimensions of occupational expertise, anticipation and optimization, personal flexibility, corporate sense and balance. The second instrument utilized in this study was Gautier and Linwood's Career Success Scale with five dimensions of job success, interpersonal success, financial success, hierarchical success and life satisfaction. Reliability of instruments was verified using Cranach Alpha which were 0.925 and 0.903 respectively for first and second one. Data analysis was performed using simple linear regression. Results showed that employability dimensions had significant effect on career success. Manuscript profile -
Open Access Article
24 - Developing and Solving two Level Lot Sizing Problem with Multi Production Methods using Vibration Damping Optimization Algorithm
Mohammad Ebrahimi Maghsod AmiriThe Capacitated Lot Sizing Problem (CLSP) consists of determining the production quantity and timing for several items on a single facility over a finite number of periods so that the demand and capacity constraints can be satisfied at a minimum cost. In this Article, d MoreThe Capacitated Lot Sizing Problem (CLSP) consists of determining the production quantity and timing for several items on a single facility over a finite number of periods so that the demand and capacity constraints can be satisfied at a minimum cost. In this Article, developing two level lot sizing problem with multi production methods is provided. The objective of the proposed model is to minimize costs. Vibration Damping Optimization (VDO) is used to solve a model. Taguchi method has been utilized to calibrate the parameters of algorithms Since the quality of solving all of the meta-innovative algorithms depends on their parameters.Then, to demonstrate the proper function of the solution method is provided, at first, experimental issues with different dimensions were generated, then it was solved by Lingo software and Vibration Damping Optimization. Finally, we compare the Lingo response and the optimization algorithm to reduce the vibration damping Optimization algorithm together in terms of the solution time. The results show that the answer to the vibration damping Optimization algorithm has a better quality than Lingo in issues of large size. Manuscript profile -
Open Access Article
25 - Developing an Optimized Portfolio Model using Modified Risk Aversion Coefficient
Roohollah Mehralizadeh shiadehi hosein didehkhani Ali Khozain arash naderianIn this paper, we propose a modification to the use of the risk aversion coefficient in optimization models, based on research literature and mathematical methods. The modified risk aversion coefficient introduced in this paper can be applied in the maximization part of MoreIn this paper, we propose a modification to the use of the risk aversion coefficient in optimization models, based on research literature and mathematical methods. The modified risk aversion coefficient introduced in this paper can be applied in the maximization part of the model without any adverse effects. By doing so, it can improve the accuracy of meta-heuristic algorithms in finding optimal solutions. To test the efficacy of our proposed model, we applied it to 30 shares of the Tehran Stock Exchange, along with a zero-risk asset, taking into account some limitations in the market. We used a genetic meta-heuristic optimization method to solve the model, and to measure its efficiency, we compared the results of the optimization process with 2500 randomly generated portfolios that were within the problem's constraints. Our results show that our model outperforms the random portfolios in terms of both risk factors and return. In conclusion, our proposed modification to the risk aversion coefficient can improve the accuracy of optimization models, and our results demonstrate its effectiveness in generating optimal portfolios in the market. Manuscript profile -
Open Access Article
26 - Optimal Design, Modeling, and Evaluation of Single-Phase Axial Flux Induction Motor with a Permanent Capacitor Using Improved Particle Swarm Optimization Algorithm (IPSO)
Amin Aboutalebi NajafabadiThe increasing application of single-phase axial flux induction motors with a permanent capacitor and their low efficiency has led to the importance of optimization of this type of motors. In this paper, by introducing the classical algorithms of design of this type of MoreThe increasing application of single-phase axial flux induction motors with a permanent capacitor and their low efficiency has led to the importance of optimization of this type of motors. In this paper, by introducing the classical algorithms of design of this type of motors, which consists of finding the dimensions of different parts of the motor and calculation of electrical parameters such as resistance and reactance, and capacitor, by introducing the proposed equivalent circuit in the permanent state to reduce the air gap of the motor, introduces the structure of optimization algorithms and then uses a genetic algorithm and improved particle swarm algorithm to optimize the design of the axial flux motor to increase efficiency, increase power factor and reduce core volume. For this purpose, a single-phase axial flux induction motor with a permanent capacitor that has considerable application in ventilation systems is investigated, and using design formulas and with the help of a circuit equivalent to the proposed permanent state, as well as using Intelligent methods such as genetic algorithm and improved particle swarm algorithm, engine optimization to increase maximum efficiency and the results are drawn in the form of torque-speed and efficiency-speed diagrams and compared with each other. Finally, the designed motor is simulated by the finite element method to verify the design algorithm, the steady-state model, the proposed optimization algorithm, and the test results. Manuscript profile -
Open Access Article
27 - Improving the Efficiency of Actual Distribution System by Allocating Multi-DG and DSTATCOM
Masoud Alilou Sajad Sadi Saeed Zamanian Javad Gholami Shahab MoshariOptimal allocation of distributed generation units and DFACTS affects the efficiency of these devices; for this reason, in this article, the simultaneous placement of distributed generation and Distributed-STATic-COMpensator (DSTATCOM) are done in the distribution syste MoreOptimal allocation of distributed generation units and DFACTS affects the efficiency of these devices; for this reason, in this article, the simultaneous placement of distributed generation and Distributed-STATic-COMpensator (DSTATCOM) are done in the distribution system. The load model is considered as a combination of various customers’ daily load patterns and sensitive to voltage-frequency. The micro turbine, wind turbine, photovoltaic and fuel cell are considered as DG units. The objective functions of the problem consist of the technical index (the voltage stability and the active and reactive power loss) and environmental index (the amount of pollutant DG unit’s gas emissions). The whale optimisation algorithm (WOA) is used to multi-objective optimize the location and capacity of devices. After applying the multi-objective WOA, the analytical hierarchy process is utilized to select one of the Pareto optimal solutions as the best location and size of devices. The proposed algorithm is implemented on the 69-bus distribution system and actual 101-bus distribution system in Khoy–Iran. The results indicate the significant effect of load models and various DG units on the efficiency of the distribution system in the presence of DSTATCOM. Moreover, the indices of the distribution system are improved considerably after applying the proposed method. Manuscript profile -
Open Access Article
28 - Structure Optimization of Locally Linear Model Tree Using Extermal Optimization
Khalil Sharifi Mohammad Reza AhmadzadehLocally Linear Model Tree (LOLIMOT) algorithm proposed by Nelles deals with local linear nearo-fuzzy models that is based on divides-and-conquer strategy that a complex modeling problem is divided to a number of smaller and thus simpler sub problems. So the characterist MoreLocally Linear Model Tree (LOLIMOT) algorithm proposed by Nelles deals with local linear nearo-fuzzy models that is based on divides-and-conquer strategy that a complex modeling problem is divided to a number of smaller and thus simpler sub problems. So the characteristic of such a neuro-fuzzy model depends on division strategy for the original complex problem. For finding the best output the algorithm divides the problem to a number of local linear models (LLMs) , then continues with finding the worst LLM and dividing it. LOLIMOT splits the local linear models into two equal halves with an axis-orthogonal decomposition strategy. In this paper a new approach based on extremeal optimization (EO) is used to optimize the structure of LOLIMOT. Simulation results show the effectiveness of the enhanced LOLIMOT to have a higher precision with optimal number of neurons. Manuscript profile -
Open Access Article
29 - Optimal PID Controller Tuning for Multivariable Aircraft Longitudinal Autopilot Based on Particle Swarm Optimization Algorithm
Mostafa Lotfi Forushani Bahram Karimi Ghazanfar ShahgholianThis paper presents an optimized controller around the longitudinal axis of multivariable system in one of the aircraft flight conditions. The controller is introduced in order to control the angle of attack from the pitch attitude angle independently (that is required MoreThis paper presents an optimized controller around the longitudinal axis of multivariable system in one of the aircraft flight conditions. The controller is introduced in order to control the angle of attack from the pitch attitude angle independently (that is required for designing a set of direct force-modes for the longitudinal axis) based on particle swarm optimization (PSO) algorithm. The autopilot system for military or civil aircraft is an essential component and in this paper, the autopilot system via 6 degree of freedom model for the control and guidance of aircraft in which the autopilot design will perform based on defining the longitudinal and the lateral-directional axes are supposed. The effectiveness of the proposed controller is illustrated by considering HIMAT aircraft. The simulation results verify merits of the proposed controller. Manuscript profile -
Open Access Article
30 - Optimum design of truss structures using particle swarm optimization considering dynamic constraints
siamak talat Hamed EbrahimzadehThese days, truss structures becomes more important due to their high performance. The benefits of frequent use of this particular type of structures include the participation of all members on dividing and distributing of loads, robustness (this means that the collapse MoreThese days, truss structures becomes more important due to their high performance. The benefits of frequent use of this particular type of structures include the participation of all members on dividing and distributing of loads, robustness (this means that the collapse of a limited number of members does not necessarily lead to the collapse of the main structures), covering large spans with minimum consumption, ease implementing, etc. Therefore, the optimization of truss structures can play a significant role on reducing costs. The particle swarm optimization algorithm has a number of advantages compared to other algorithms, which make it superior; some of these benefits is as: a small number of regulatory parameters, good use of required memory and high speed of convergence. The frequency resonances of the structures were selected as the constraints due to prevent large deformation and thereby prevent structural damage. The results of the new proposed algorithm is far better than the original PSO algorithm and other algorithms used in this research in both the rate of convergence and the quality of solutions for finding optimum design of truss structures considering dynamic constraints. Manuscript profile -
Open Access Article
31 - مقدار انرژی پیوسته مولکول 3-آمینو-4-نیترامین فورازان با تکنیکهای بهینهسـازی مدرن
Ahmet Sahiner Fatih Ucun Sumeyya Komanتغییـر مقـدار انـرژی سـازگار مولکـول (C2N4O3H2) با دو زاویه پیچشـی ابتدا بـا اسـتفاده از نظریـه تابع چگالـی (DFT) با تابع همبسـتگی -Lee-young par و31-6 مجموعـه پایـه بـر مجموعـهای در برنامه گاوسـی محاسـبه شـد. و پـس از آن، ایـن دادههـا گسسـته به دسـت آمـده با اسـتفاده ا Moreتغییـر مقـدار انـرژی سـازگار مولکـول (C2N4O3H2) با دو زاویه پیچشـی ابتدا بـا اسـتفاده از نظریـه تابع چگالـی (DFT) با تابع همبسـتگی -Lee-young par و31-6 مجموعـه پایـه بـر مجموعـهای در برنامه گاوسـی محاسـبه شـد. و پـس از آن، ایـن دادههـا گسسـته به دسـت آمـده با اسـتفاده از منطق مدلسـازی فـازی (FLM) و شـبکه عصبـی مصنوعـی (ANN) پیوسـته سـاخته شـد. این امـر بـه مـا اجـازه پیش بینـی در مورد دادههای تسـت نشـده و، به دسـت آوردن مقـدار انرژی بهینهسـازی شـده وابسـته بـه دو زاویـه چرخش با هزینه محاسـباتی منطقـی، کارایـی زیـاد و دقـت بـالا را میدهـد . نتایـج بـه دسـت آمـده بـا نتایج DFT بـا اسـتفاده از تجزیه و تحلیل رگرسـیون مقایسـه شـدند. Manuscript profile -
Open Access Article
32 - یک روش ترکیبی جدید گرادیان مزدوج مبتنی بر معادله سکانت برای حل مسائل بهینه سازی مقیاس بزرگ
نصیرو صلیحو Mathew Odekunle Mohammed Waziri Abubakar Haliluانواع زیادی از الگوریتم های گرادیان مزدوج وجود دارد. به منظور بهره گیری از ویژگی های جذاب روش های لیو و استوری (LS) و سکانت مزدوج (CD) و روش گرادیان مزدوج ، ما ترکیبی از این روش ها که در آن پارامتر به عنوان ترکیبی محدب محاسبه می شود و به ترتیب پارامتر گرادیان (برو Moreانواع زیادی از الگوریتم های گرادیان مزدوج وجود دارد. به منظور بهره گیری از ویژگی های جذاب روش های لیو و استوری (LS) و سکانت مزدوج (CD) و روش گرادیان مزدوج ، ما ترکیبی از این روش ها که در آن پارامتر به عنوان ترکیبی محدب محاسبه می شود و به ترتیب پارامتر گرادیان (بروزرسانی) از معادله Secant بدست آمده است را پیشنهاد می کنیم. الگوریتم جهت نزول را ایجاد می کند و هنگامی که فشردگی تگرار می شود جهت شرایط مناسب نزول را برآورده می کند. گزارش نتایج عددی نشان دهنده کارایی روش ما است.طرح محاسباتی ترکیبی عملکرد بهتری دارد یا قابل مقایسه با الگوریتم گرادیان مزدوج شناخته شده است. همچنین نشان می دهد که روش ما در سطح جهانی با استفاده از شرایط ولف قوی همگراست. Manuscript profile -
Open Access Article
33 - الگوریتم های فراابتکاری برای حل مشکل امکانات ترمینال در مقیاس واقعی
مهدی فضلی فرزین مدرس خیابانی بهروز دانشیان -
Open Access Article
34 - الگوریتم بهینه سازی چندهدفه کرم شب تاب برای طراحی جانمایی کارگاه ساختمانی
Abolfazl Ghadiri داود صداقت شایگان علی اصغر امیرکاردوستاهمیت ایمنی در طرح چیدمان سایت ساخت و ساز یک نیاز ضروری برای بهبود مدیریت پروژه ساختمانی است. در مطالعات قبلی تابع هدف، ایمنی بدون تجزیه و تحلیل عوامل خطر در نظر گرفته شده است. فراابتکاری ها به طور گسترده ای برای حل مسائل برنامه ریزی چیدمان سایت ساخت و ساز استفاده می شو Moreاهمیت ایمنی در طرح چیدمان سایت ساخت و ساز یک نیاز ضروری برای بهبود مدیریت پروژه ساختمانی است. در مطالعات قبلی تابع هدف، ایمنی بدون تجزیه و تحلیل عوامل خطر در نظر گرفته شده است. فراابتکاری ها به طور گسترده ای برای حل مسائل برنامه ریزی چیدمان سایت ساخت و ساز استفاده می شود. الگوریتم کرم شب تاب (FA) به عنوان روش بهینه سازی چند هدفه برای طراحی و بهینه سازی دو تابع هدف ایمنی و هزینه کل استفاده می شود. توابع هدف ایمنی (به دلیل خطرات بالقوه ناشی از منابع خطرناک و جریان های متقابل) اتصال تأسیسات موقت با در نظر گرفتن کاهش هزینه کل. یک مطالعه موردی برای پی بردن به دقت مدل پیشنهادی ارائه شده است. در نهایت، عملکرد دو الگوریتم فراابتکاری به نامهای الگوریتم فایرفلای (FA) و بهینهسازی کلونی مورچهها (ACO) از نظر اثربخشی در حل مشکل طراحی سایت ساختوساز مورد مقایسه قرار گرفتهاند. نتایج نشان می دهد که FA بهتر از الگوریتم ACO عمل می کند. Manuscript profile -
Open Access Article
35 - Estimation of loan repayment loss in Sarmayeh Bank using weed optimization meta-heuristic algorithm
zahra Rahmani Mohammad Ebrahim Mohammadpoor Zarandi Mohammadali keramatiLiquidity management has been one of the biggest challenges facing the banking system in Iran in the acute inflation conditions in recent years. Facilities granted by banks, regardless of inflationary conditions, usually lead to hidden losses in repayment of loans, resu MoreLiquidity management has been one of the biggest challenges facing the banking system in Iran in the acute inflation conditions in recent years. Facilities granted by banks, regardless of inflationary conditions, usually lead to hidden losses in repayment of loans, resulting in reduced profitability and the risk of inability to meet obligations, resulting in the risk of bankruptcy. The present study aims to estimate the loan repayment loss in Sarmayeh Bank using the weed optimization meta-heuristic algorithm. In the present study, a model was designed to examine the loan repayment loss. Also, to compare the calculated results using the proposed heuristic formula and the income of the granted financial facilities in terms of loan repayment loss prediction, weed optimization meta-heuristic algorithm was used. The results showed that there is a negative correlation between loan repayment losses and the growth of Sarmayeh Bank profitability in high inflation conditions. Also, comparing the loan loss prediction between the calculated results using the proposed heuristic formula, the number predicted by the weed optimization algorithm and the income of the granted financial facilities showed that the loan repayment loss using the weed optimization meta-heuristic algorithm can be calculated. Manuscript profile -
Open Access Article
36 - Designing a credit portfolio optimization model in the banking industry using a meta-innovative algorithm
ali asghar tehrani poor Ebrahim Abbasi Hosein Didehkhani arash naderianThe purpose of this study is to design a credit portfolio optimization model in the banking industry using a meta-innovative algorithm. Risk is one of the basic concepts in financial markets that has a certain complexity. Due to the lack of a clear picture of risk reali MoreThe purpose of this study is to design a credit portfolio optimization model in the banking industry using a meta-innovative algorithm. Risk is one of the basic concepts in financial markets that has a certain complexity. Due to the lack of a clear picture of risk realization, financial markets need risk control and management approaches. The present study is a descriptive survey in terms of data collection and applied in terms of purpose. The statistical population of this research includes all facility files of the last 10 years as well as the financial statements of Ansar Bank branches affiliated to Sepah Bank, which were selected by census method. The risk criteria used in the models are: fuzzy risk value, absolute value of fuzzy downward deviations and half entropy. Research models were implemented using multi-objective particle swarm optimization algorithm. The software used in conducting research is MATLAB software. The results show that the performance of the fuzzy risk-averaged model is better than the other two models in evaluating optimal portfolios. Therefore, the use of the above model in credit basket optimization is recommended. Manuscript profile -
Open Access Article
37 - Portfolio Optimization Using the Whale Algorithm with Expected Shortfall as the Measure of Risk
saeed fallahpour sepehr asefi sima fallahtafti MohammadReza BagherikazemabadPortfolio Selection is one of the most important decisions that institutional investors have to face. Markowitz was the first to introduce risk into the portfolio selection decision by introducing the Mean-Variance Model. This created one of the most importa MorePortfolio Selection is one of the most important decisions that institutional investors have to face. Markowitz was the first to introduce risk into the portfolio selection decision by introducing the Mean-Variance Model. This created one of the most important fields in finance, that is Portfolio Optimization and finding the efficient frontier. In the next researches, adding real world constraints to the model broadened this field. With increasing the number of assets or the constraints, Portfolio Optimization becomes an NP-hard problem which is impossible to solve with derivative-based methods, therefore, numerical and metaheuristic methods should be used for solving it. The aim of this research is optimizing portfolio using Whale optimization algorithm. This metaheuristic algorithm is inspired by the behavior of Whales and was introduced in 2016. This research implements the algorithm in the top 50 index in Tehran Stock Exchange and tries to find the efficient portfolio in this index. We also compare the performance of this method to two other metaheuristic algorithms and explain the advantages of the proposed method in portfolio optimization. Manuscript profile -
Open Access Article
38 - Misevaluation and Behavioral Biases in the Tehran stock exchange
Jamal Tavosi Jamal Tavosi Aminreza KamalianAccording to efficiency market hypothesis security prices respond quickly to new information and accurately reflect their fundamental values. More recent work indicates that market frictions and the psychological limitations of traders can cause asset prices to deviate MoreAccording to efficiency market hypothesis security prices respond quickly to new information and accurately reflect their fundamental values. More recent work indicates that market frictions and the psychological limitations of traders can cause asset prices to deviate from their fundamental values for a considerable length of time. To investigate theoretical concepts, the composite error model and event study approach and for specification model Particular Swarm Optimization were used in this study. The results from Coelli one-sided likelihood ratio test in the event period shows that there are the biases in IKCO’s returns. This study develops an empirical method that tests for and estimates the degree of valuation bias. Being better able to detect valuation bias reveals profit opportunities and may improve the efficiency of financial markets if it sufficiently changes trader behavior. Manuscript profile
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