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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 - Designing Automatic Re-balancing Model Using Technical Analysis Concept of Divergence
S. M. Lale Sajjadi S. Hojjat Vakili S. Babak EbrahimiThe classical efficient market hypothesis states that it is not possible to beat the market by developing a strategy based on historical price series. In this paper we propose a profitable automatic trading system based on the divergence definition in relative strength MoreThe classical efficient market hypothesis states that it is not possible to beat the market by developing a strategy based on historical price series. In this paper we propose a profitable automatic trading system based on the divergence definition in relative strength index and using other technical analysis tools which presents empirical evidence confronting the classical efficient market hypothesis. In order to validate the developed solution an extensive evaluation was performed, comparing the designed strategy against the market itself and several other investment methodologies. An intraday database comprised of 59 symbols from NYSE in The time span 2010 to 2016 was employed. The whole sample is categorized over two sub-periods, training and widening its validity. By enjoying Meta-heuristic algorithms the rules in the first sub-period was improved. Then, in the second division the improved model was evaluated. The results indicates that this model improved predictability power and its performance is better than buy and hold and random strategies Manuscript profile -
Open Access Article
3 - Designing a Biodiesel Supply Chain Network by Considering Environmental FactorsUnder Uncertainty Conditions and solving it with the MOPSO algorithm
gholamreza jandaghi mohammad reza fathi mohammad hasan maleki Meysam MolaviBackground and Objective: Increasing concerns about energy and greenhouse gas emissions from fossil fuel consumption have encouraged many researchers to be involved in developing sources of renewable energies. Biodiesel derived from biomass can play a crucial role in th MoreBackground and Objective: Increasing concerns about energy and greenhouse gas emissions from fossil fuel consumption have encouraged many researchers to be involved in developing sources of renewable energies. Biodiesel derived from biomass can play a crucial role in this context. The main objective of this paper is to present a mathematical programming model for the biomass supply chain. Material and Methodology: Researcher through library research and preparing a questionnaire to estimate parameters and data associated with the uncertainty of parameters and then through interviews, expert opinions about the limits and changes to the decision-making parameters have collected. Then a fuzzy multi-objective mixed integer programming model is presented that model to minimize costs, minimize environmental impact and minimize the time of delivery of product in Biodiesel Supply Chain. Findings: After running the model, increasing objective function is to minimize the total cost, minimize environmental impact and minimizing the time the product reaches the customer contact temperature limits for different values were obtained. Discussion and Conclusion: In this study, the proposed mathematical programming model is solved with the MOPSO algorithm. The results indicate the location and capacity of the facility, the amount of biodegradable and glycerin production, and the amount of extracted Jatropha oil and refined waste oils. Manuscript profile -
Open Access Article
4 - A Trust-based Recommender System Using an Improved Particle Swarm Optimization Algorithm
Sajad Ahmadian Mohammad Hossein OlyaeeIntroduction: Recommender systems are intelligent tools to help users find their desired information among a large number of choices based on their previous preferences in a way faster than search engines. One of the main challenges in recommender systems is the sparsit MoreIntroduction: Recommender systems are intelligent tools to help users find their desired information among a large number of choices based on their previous preferences in a way faster than search engines. One of the main challenges in recommender systems is the sparsity of the user-item rating matrix. This means that users mainly tend to express their opinions about a few items, leading to a large portion of the user-item rating matrix being empty. Trust-based recommender systems aim to alleviate the sparsity problem using trust relationships between users. Trust relationships can be used to calculate similarity values between users and determine the nearest neighbors set for the target user. However, the efficiency of trust-based recommender systems depends on the correct selection of neighboring users for the target user based on the similarity values between users. Method: In this paper, a novel trust-based recommender system is proposed based on an improved particle swarm optimization algorithm. To this end, first, the similarity values between users are calculated based on the user-item rating matrix and trust relationships. Then, the improved particle swarm optimization algorithm is used to optimally weight the neighboring users of the target user. The main purpose of this algorithm is to assign an optimal weight to each user in the nearest neighbor set of the target user to predict the unknown items accurately. After the optimal weighting of neighboring users, unknown ratings are predicted for the target user. Results: The proposed method is evaluated on a standard dataset in terms of mean absolute error, root mean square error, and rate coverage metrics. Experimental results demonstrate the high efficiency of the proposed method compared to other methods. Discussion: We use the genetic algorithms operators and chaos-based asexual reproduction optimization algorithm to improve the original version of the particle swarm optimization algorithm. The genetic algorithms operators increase the exploration mechanism of the particle swarm optimization algorithm, leading to a decline in the probability of tapping into local optima. Moreover, the chaos-based asexual reproduction optimization algorithm is applied to the best solution to further search the area around the best solution. Manuscript profile -
Open Access Article
5 - بررسی عملکرد الگوریتم شاهین هریس در بهینهسازی مخزن سد
کبری رنجوری مهدی اژدری مقدم سید آرمان هاشمی منفرد سیما اوحدی در هر منطقه ­ای بر اثر کمبود نزولات جوی و با هر نوع آب و هوایی امکان رویداد پدیده خشکسالی وجود دارد. این پدیده به عواملی مانند دمای بالا، رطوبت نسبی پایین، ضریب پایین ذوب برف، باد و کمبود بارش بستگی دارد. بهره ­برداری بهینه مخازن با در More در هر منطقه ­ای بر اثر کمبود نزولات جوی و با هر نوع آب و هوایی امکان رویداد پدیده خشکسالی وجود دارد. این پدیده به عواملی مانند دمای بالا، رطوبت نسبی پایین، ضریب پایین ذوب برف، باد و کمبود بارش بستگی دارد. بهره ­برداری بهینه مخازن با در نظرگرفتن اهداف مهم چندگانه در کنار یکدیگر و بهصورت همزمان از اهمیت بالایی برخوردار است و به همین جهت لازم است حجم مخزن در هر ماه مدیریت شود؛ زیرا کارایی مخزن در کنترل سیلاب به حجم مخزن و مشخصات ژئومتری آن و سرریز بستگی دارد. در این مطالعه با استفاده از نرمافزار MATLAB و یک الگوریتم بهینه شاهین هریس دادههای سد امیرکبیر کرج به جهت یافتن میزان بهینه برداشت از مخزن سد، نوشته شد و الگوریتم شاهین هریس مورد ارزیابی قرار گرفت. الگوریتم مبتنی بر جمعیت، فرآیند جست­­جو را در دو مرحله اکتشاف و بهره­ برداری انجام میدهد. در الگوریتم شاهین هریس پارامترهایی وجود دارد که تغییر در مقدار آنها بر عملکرد این الگوریتم تأثیر می ­گذارد. در این مطالعه مقدار کمینه تابع هدف در الگوریتم شاهین هریس بررسیشد. با افزایش تعداد تکرارها، مقدار تابع هدف بهبود پیدا می ­کند و بهترین مقدار تابع هدف، در تکرار 64000 با مقدار 8934/25 بود که بهترین عملکرد الگوریتم در این تکرار بهدستآمد. Manuscript profile -
Open Access Article
6 - The new MILP mathematical model for optimization of complex assembly lines with the ABC-PSO method
neda mozaffari HASAN MEHRMANESH mahmoud mohammadiThe problem of balancing assembly lines is one of the optimization problems that have been studied by many researchers. However, after six decades of research and development, there is a profound gap between academic studies in this area and the practical applications o MoreThe problem of balancing assembly lines is one of the optimization problems that have been studied by many researchers. However, after six decades of research and development, there is a profound gap between academic studies in this area and the practical applications of the assembly line balancing problem in the real industry environment. For this reason, this study aimed to balance the complex assembly lines in order to reduce the cost of manpower and reduce the number of workstations. To solve the problem from the dataset consisting of 7 workstations and 70 tasks and the time to solve 500 seconds and the time of performing each activity including 260 specific activities, two general approaches are used to determine the prerequisite relationships. Gams model software is resolved. Then the problem is solved once again with the modified honeycomb algorithm in MATLAB software and finally solved by the new hybrid honeycomb algorithm with PSO method and finally the obtained values of the objective function of both methods are combined. Have been compared and the results show that the hybrid honeycomb algorithm is optimized at the same early stages of optimization and its objective function value reaches its minimum value and also obtained the least amount of constraint violation and shows cost and cost reductions. Reduces workstations to 3. Manuscript profile -
Open Access Article
7 - An Effective Frog-leaping Algorithm to Minimize the Completion Time Problem of the Resource-constrained Projects
Alireza Haji Akhondi Gholam Reza Tavakoli Peyman Akhavan Manouchehr ManteghiFrog leaping algorithm combination (SFLA) is an algorithm based on memetic Meta-heuristic. Created in recent years by Eusuff and Lansey, SFLA algorithm works in a way that the frog groups search for food. The development of memetic algorithms for local search method is MoreFrog leaping algorithm combination (SFLA) is an algorithm based on memetic Meta-heuristic. Created in recent years by Eusuff and Lansey, SFLA algorithm works in a way that the frog groups search for food. The development of memetic algorithms for local search method is similar to the activities of a frog among subgroups. SFLA uses a combination of strategy and provides the ability to exchange messages in local search. Frog leaping algorithm combines the advantages of particle swarm optimization algorithm and memetic development (PSO). Since the resource-constrained project scheduling problem is the timing issue, scheduling issues in the construction sites and plants is highly considered. One of the main duties of the project scheduling and project management is to reduce the completion time. Because of the resource constraints and precedence relationships between activities, project scheduling problem is difficult. In this paper, the algorithm performance LeapFrog (SFLA) is applied to reduce the project scheduling problems with resource constraints. The findings prove the robust performance of the new meta-heuristic algorithm. Manuscript profile -
Open Access Article
8 - the use of the tabu search metaheuristic to solve location problems: a review
Alireza BitarafIn this paper, a detailed review of the application of the Tabu search method on location problems is reviewed. For this purpose, first the concept of locationing and different types of location problems are introduced and then the components of the Tabu search method a MoreIn this paper, a detailed review of the application of the Tabu search method on location problems is reviewed. For this purpose, first the concept of locationing and different types of location problems are introduced and then the components of the Tabu search method are described in detail. The purpose of locationing is to find new suitable locations for setting up facility location. Today, increasing competition between companies has made it very important to study location problems. There are various methods for solving location problems. In recent decades, various metaheuristic methods have been introduced to solve such problems. Ultra-innovative methods use innovative ideas to solve problems with large data and dimensions. One of the metaheuristic methods is the tabu search algorithm, which is based on local search and gives desirable results in solving location problems. This algorithm has various components which are introduced in detail in this paper. The components that some researchers have added to this method to improve its performance are also introduced. In this paper, a detailed review of the application of the Tabu search method on location problems is reviewed. For this purpose, first the concept of locationing and different types of location problems are introduced and then the components of the Tabu search method are described in detail. The purpose of locationing is to find new suitable locations for setting up facility location. Today, increasing competition between companies has made it very important to study location problems. There are various methods for solving location problems. In recent decades, various metaheuristic methods have been introduced to solve such problems. Ultra-innovative methods use innovative ideas to solve problems with large data and dimensions. One of the metaheuristic methods is the tabu search algorithm, which is based on local search and gives desirable results in solving location problems. This algorithm has various components which are introduced in detail in this paper. The components that some researchers have added to this method to improve its performance are also introduced. Manuscript profile -
Open Access Article
9 - OPTIMIZING U-SHAPED MIXED ASSEMBLY LINES WITH A META- HEURISTIC GRASSHOPPER OPTIMIZATION ALGORITHM
Neda Mozaffari Hasan Mehrmanesh Mahmoud MohammadiFailure to achieve a balanced production system means not fully utilizing the capabilities of the production system, and because of the high cost of production systems, balancing these systems is one of the most important concerns of production managers. Is. For this re MoreFailure to achieve a balanced production system means not fully utilizing the capabilities of the production system, and because of the high cost of production systems, balancing these systems is one of the most important concerns of production managers. Is. For this reason, this study aimed to balance the complex assembly lines in order to reduce the cost of manpower and reduce the number of workstations. There are two general approaches to problem solving, To evaluate the problem under different conditions two problems of medium and large size are solved. First, an intermediate problem is solved by the exact method through the Gaussian software (GAMS) and the Salon Baron (BARON). Then again the intermediate problem is solved with the grasshopper meta-algorithm and their results are compared with the precise method and by this the accuracy and accuracy of the meta-metric method is measured so that it can be used to solve the large size problem. Finally, the values equal to the Grasshopper Algorithm Target Function and the Gaussian Target Function software show that the algorithm performs well, resulting in a large problem solved by the Grasshopper Metabolic Algorithm, resulting in cost savings and reduced workstations. Manuscript profile -
Open Access Article
10 - Designing a closed-loop supply chain mathematical model with an emphasis on empowering environmental capabilities and increasing profitability (military products case study)
abolfazl sadeghi Keyvan Sahgholian Akbar AlemtabrizThe main solution for companies to simultaneously achieve economic and environmental goals is to implement a closed loop supply chain. The main goal of this research is to design a mathematical model to empower the environmental capabilities and profitability of the clo MoreThe main solution for companies to simultaneously achieve economic and environmental goals is to implement a closed loop supply chain. The main goal of this research is to design a mathematical model to empower the environmental capabilities and profitability of the closed loop supply chain in military industries. The presented model is a 4-objective model, the first objective of which is to minimize emissions, the second objective is to minimize environmental waste, the third objective is to minimize cost, and the fourth objective is to minimize the risk of raw material supply. After designing the model, validation of the model has been done by solving it in small dimensions and then using four algorithms NSGAII, MOPSO, MOACO, MOSA to solve the model in medium and large dimensions and its results have been compared. Based on the results, the parameters of the model have been adjusted and the response of the model to different parameters has been investigated. The results show that simultaneous consideration of environmental and economic dimensions in the parameters leads to the improvement of the performance of the closed loop supply chain in terms of empowering the environmental capabilities and profitability. Manuscript profile -
Open Access Article
11 - Designing and explaining the pricing model in the four-level closed loop supply chain considering the uncertainty in the paper industry
Mahdi Alizadeh Beromi Mohammad Ali Afshar Kazemi Mohammadali Keramati abbas Toloie ashlaghiRecently, the supply chain of perishable goods, have been considered due to their impact on human life. On the other hand, in the packaging industry, considering paper as a primary and perishable material due to the nature of water absorption, severe rotting in front of MoreRecently, the supply chain of perishable goods, have been considered due to their impact on human life. On the other hand, in the packaging industry, considering paper as a primary and perishable material due to the nature of water absorption, severe rotting in front of sunlight, flammability and turning to ash and finally affecting the final quality of the product produced from this issue. It is not excluded, it has attracted more attention. The high level of speed of changes and ambiguity in decisions has made it impossible to predict the future conditions of supply chains. Therefore, the design and use of a mathematical model for the design of the closed-loop supply chain network, taking into account the optimal pricing of products, the return rate and demand, along with taking into account the wastage of materials in the system, is strongly needed. At first, the supply chain of the paper-cardboard industry was designed and modeled with mixed integer programming, then due to the high volume of calculations and data of the problem, we can't receive exact solution approaches, the innovative approach of searching for harmony was used for the solution. . The problem is a single-objective model that minimizes system costs by considering environmental considerations. The present research shows that the price increase has a positive effect on the product return rate and reducing the level of product corruption. Finally, to validate the model, the numerical solution of a closed loop network has been done in this industry. Manuscript profile -
Open Access Article
12 - Predicting product choice by customers based on neuromarketing with Chaotic salp swarm algorithm
Marzieh Maleki Zahra Dasht LaliUnderstanding how consumers make decisions is one of the important things in customer behavior that is addressed by neuromarketing. The purpose of this article is to present a new solution in neuromarketing by receiving brain signals and extracting and selecting importa MoreUnderstanding how consumers make decisions is one of the important things in customer behavior that is addressed by neuromarketing. The purpose of this article is to present a new solution in neuromarketing by receiving brain signals and extracting and selecting important features and classification to increase the prediction of product selection by customers. In this article, brain signals from twenty-five participants who have seen the products have been received and characterized by the high-order spectrum method. In order to select the best features, in this article, the swarm algorithm of salp chaos has been presented, which can identify the effective features with high search power, and for the final prediction, different classifications have been used in the form of multiple learning. In the proposed model, the high-order spectra method was applied in extracting the phase information of the electroencephalogram signal in order to investigate the relationship between liking and disliking the product, which included more than seven hundred features. Then feature selection was used with the improved Salp swarm algorithm with logistic chaos mapping and the features were reduced from 742 to 198 features. The results showed that the proposed model was able to have an average accuracy of 75.99% in detecting the choice of users in all products, which shows a 3.75% improvement in the results compared to similar researches. Manuscript profile -
Open Access Article
13 - .
Saeed Aghasi Akram KarimpourFinancial investors' access to the most favorable position is achieved when the maximum rate of return with a certain risk or the minimum risk with a certain rate of return is created. To find such a situation, various linear and nonlinear mathematical methods such as a MoreFinancial investors' access to the most favorable position is achieved when the maximum rate of return with a certain risk or the minimum risk with a certain rate of return is created. To find such a situation, various linear and nonlinear mathematical methods such as a wide range of meta-heuristic algorithms are used. The main purpose of this study is to investigate and analyze the use of flower pollination algorithm and compare it with Markowitz model in accurately identifying and selecting the optimal portfolio of companies listed on the Tehran Stock Exchange. In the first stage, 50 companies and in the second stage, 10 companies were selected as the top companies among the companies listed on the Tehran Stock Exchange, which had a 5-year activity in 2015-2016. The new flower pollination algorithm was compared. The results showed that the flower pollination algorithm has better performance both in terms of return and investment risk. Manuscript profile -
Open Access Article
14 - Presenting a multi-objective mathematical model integrating production scheduling and maintenance considering the limited access to production resources in conditions of uncertainty and optimization with multi-objective genetic algorithm
محمد شریف زادگان محمدرضا حیدری کورش پوری عادل پورقادر چوبر میلاد ابوالقاسمیانIn production and industrial systems, the integrated planning of production and operations is very important. Responding quickly to the needs of customers, diversity, reliability and cost of equipment and machines, due to the extensive limitations in production resource MoreIn production and industrial systems, the integrated planning of production and operations is very important. Responding quickly to the needs of customers, diversity, reliability and cost of equipment and machines, due to the extensive limitations in production resources, competitiveness and gaining market share in conditions of uncertainty, there is a need to plan the units. be done in an integrated manner. In most of the production units, effective information is at an unfavorable level of coordination and exchange with other activities. The result of such activities is nothing but a waste of resources and the emergence of an insular culture in the organization. Therefore, in this research, a MIP mathematical model was modeled in line with the planning of production, maintenance in Maron Company. The objectives of the proposed model are to minimize production costs and maintenance costs with limited production resources. dependents such as maintenance) was used by the innovative method of genetics. The results of the modeling evaluation showed that the detailed and ultra-innovative solution provided has improved the company's production by more than 7%. Manuscript profile -
Open Access Article
15 - بررسی عملکرد الگوریتم GRASP درانتخاب پرتفوی بهینه ( با لحاظ محدودیت کاردینالیتی
میثم امیری محمدحسن ابراهیمی سروعلیا هما هاشمی -
Open Access Article
16 - Portfolio optimization in capital market bubble space, application of bee colony algorithm
Iman Mohammadi Hamzeh Mohammadi Khashoei arezoo aghaei chadeganiThe existence of bubbles in the market,especially the capital market,can be a factor in preventing the participation of investors in the capital market process and the correct allocation of financial resources for the economic development of the country.On the other han MoreThe existence of bubbles in the market,especially the capital market,can be a factor in preventing the participation of investors in the capital market process and the correct allocation of financial resources for the economic development of the country.On the other hand,due to the goal of investors in achieving a high return portfolio with the least amount of risk,it is necessary to pay more attention to these markets In this study,in order to maximize returns and minimize investment risk,an attempt was made to create an optimal portfolio in conditions where the capital market has a price bubble.According to the purpose,the research is of applied type,and in terms of data,quantitative and post-event,and in terms of analysis,is descriptive-correlation.In order to identify bubble months in the period from2015to2019in Tehran Stock Exchange,sequence tests and skewness and kurtosis tests were used and after identifying bubble periods,artificial bee colony algorithm was used to optimize the portfolio.The results indicate the identification of 10 periods with a price bubble in the study period.Also,in portfolio optimization, selected stock portfolios are formed with maximum returns and minimum risk.This research will be a guide for investors in identifying bubble courses and how to form an optimal portfolio in these conditions. Manuscript profile
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