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Open Access Article
1 - Prediction of Stream Flow Using Intelligent Hybrid Models in Monthly Scale (Case study: Zarrin roud River)
Babak Mohammadi Roozbeh MoazenzadehBackground and Objective: Selecting appropriate inputs for intelligent models are important because it reduces the cost and saves time and increases accuracy and efficiency of its models. The aim of the present study is the use of Shannon entropy to select the optimum c MoreBackground and Objective: Selecting appropriate inputs for intelligent models are important because it reduces the cost and saves time and increases accuracy and efficiency of its models. The aim of the present study is the use of Shannon entropy to select the optimum combination of input variables in the simulation of monthly flow by meteorological parameters. Method: In this study, meteorological data and monthly time series of discharge of Zarrinrood River (Safavankeh Station) in East Azarbaijan from 1336 to 2015 were used. The meteorological parameters and the month of the year were considered as inputs in the entropy method to determine the effective composition. Results: Shannon entropy results showed that the rainfall parameters, month of year and temperature provide better results for modeling. The simulations were performed using intelligent hybrid models of particle swarm hybrid algorithm and hybrid simulation hybrid algorithm. Discussion and Conclusion: The results showed that among these models with the same input structure, the hybrid algorithm simulation based on the support vector machine had better performance for simulating the flow rate compared to other intelligent hybrid models. The results also show that the entropy method is good for selecting the best input combination in smart models. Manuscript profile -
Open Access Article
2 - A novel Meta-Heuristic method for solving an extended Markowitz Mean–Variance portfolio selection model
Gholamreza Eslami Bidgoli Ehsan Tayebi SaniThis paper presents a novel Meta-Heuristic method for solving an extended Markowitz Mean–Variance portfolio selection model. The extended model considers Value-at-Risk (VaR) as risk measure instead of Variance. Depending on the method of VaR calculation its minimi MoreThis paper presents a novel Meta-Heuristic method for solving an extended Markowitz Mean–Variance portfolio selection model. The extended model considers Value-at-Risk (VaR) as risk measure instead of Variance. Depending on the method of VaR calculation its minimizing methodology differs. if we use Historical Simulation which is applied in this paper then the curve would be non-convex. On the other hand the Mean-VaR model here includes three sets of constraints: bounds on holdings, cardinality and minimum return which cause a Mixed Integer Quadratic Programming Problem. The first set of constraints guarantee that the amount invested (if any) in each asset is between its predetermined upper and lower bounds. The cardinality constraint ensures that the total number of assets selected in the portfolio’s equal to a predefined number. Because of above mentioned reasons, in this paper, we propose a new Meta-Heuristic approach based on combined Ant Colony Optimization (ACO) method and Genetic Algorithm (GA). The computational results show that the proposed Hybrid Algorithm has the ability to optimized Mean-VaR portfolio for small portfolio Manuscript profile -
Open Access Article
3 - Using a Hybrid NSGA-II to Solve the Redundancy Allocation Mmodel of Series-Parallel Systems
Mohammadreza Shahriari -
Open Access Article
4 - Hybrid PSOS Algorithm For Continuous Optimization
A. Jafarian B. Farnad -
Open Access Article
5 - The Inverse Method of Damage Detection using Swarm Life Cycle Algorithm (SLCA) via Modal Parameters in Beam Like Structures
Alireza Arghavan Ali Ghoddosian Ehsan Jamshidi -
Open Access Article
6 - A New Approach to The University Course Timetabling Problem based on Clustering Algorithms & Fuzzy Multi-Criteria Decision Making
behzad mohammadkhani hamed Babaei, davod eskandari mohammadreza hasanzadeh Introduction: The UCTTP problem is a hybrid optimization problem that belongs to the NP-hard class, hence determining the optimal or analytical solution of this problem is challenging. This problem, which occurs at the beginning of the university semester, involve More Introduction: The UCTTP problem is a hybrid optimization problem that belongs to the NP-hard class, hence determining the optimal or analytical solution of this problem is challenging. This problem, which occurs at the beginning of the university semester, involves allocating events (courses, faculty, and students) to a number of time slot and specific number of rooms. The UCTTP problem must satisfy both hard and soft constraints so that feasible time tables are obtained after complete and correct satisfaction of all hard constraints. Satisfaction of soft constraints is merely for the quality improvement of the produced feasible time tables and unlike hard constraint their satisfaction is not mandatory. Another important issue associated with this problem is the multiplicity and variety of constraints (hard and soft) that are completely case dependent. The soft constraints considered by each solution (schedule) are evaluated by the penalty function, which is obtained by a summation operator. In this operator, a weight is assigned to each soft constraint, and according to these weights, a penalty function is obtained, the output of the penalty function is used in the objective function which yields final solutions. After obtaining all the final solutions, the schedule tables that have no collisions, that is, satisfy all the strict constraints, and secondly, have a higher value in terms of the value of the objective function are selected.Method: According to the simulation results, it can be said that in using clustering algorithms, the efficiency of fuzzy C-clustering algorithm in minimizing resource loss (surplus) and descending satisfaction of soft constraints of common lecturers of faculties is higher than funnel clustering algorithm and the K-mean.Findings: The optimal ratio of the number of applied penalties for the violations of lecturers’ soft constraints and the percentage of violations of lecturers among the fuzzy multi-criteria decision comparison algorithms, local search and genetics, as well as the combination of these algorithms are related to the combination of two comparison algorithms (i.e. fuzzy multi-criteria decision making and local search).Discussion and Conclusion: We observed that with regards to the percentage of satisfaction of soft constraints of common lecturers, the combination of local search algorithms with C-fuzzy clustering shows the best performance and f fuzzy multi-criteria decision comparison algorithm has the worst performance. Manuscript profile -
Open Access Article
7 - Design a Hybrid Model of Multi-Criteria Decision-Making Techniques for Ranking the Bank Branches
Pegah Aminijam Milad Jasemi ZarganiDue to the importance of ranking bank branches and the lack of a comprehensive ranking model, which can lead to improved performance of the bank and the country economic growth, offering a hybrid multiple criteria decision-making (MCDM) model for ranking among bank bran MoreDue to the importance of ranking bank branches and the lack of a comprehensive ranking model, which can lead to improved performance of the bank and the country economic growth, offering a hybrid multiple criteria decision-making (MCDM) model for ranking among bank branches is necessary. However, with the passing of time, MCDM methods have helped a lot in the rankings. But the choice of which methods is accepted as the best solution is always an ambiguity. Since the comprehensive hybrid algorithm that can identify the top branches not provided, yet. This research is trying to achieve the final ranking of the branches. Thus the optimal solution is to introduce a hybrid algorithm that determines the optimal weights of the MADM methods by a linear model. This approach is especially applicable when we cannot prefer any ranking method to others. Thus, in this paper, the criteria weights are obtained using DEMATEL and ANP methods. Afterward, the bank branches are ranked using TOPSIS, VIKOR, PROMETHEE II, SAW, WPM and DEA methods, each of which is important and significant. Finally, using proposed hybrid algorithm the optimal weights of different methods and the ranks are calculated. Manuscript profile -
Open Access Article
8 - The impact of meta-heuristic hybrid algorithm analysis on portfolio diversification and excess return of investment funds and its role in Islamic financial marketing
Narges Salehi Azari Shadi Shahverdiani Gholamreza ZomorodianThe purpose of this research is to investigate the impact of meta-heuristic hybrid algorithm analysis on portfolio diversification and excess returns of investment funds. In terms of method, the current research is a part of correlation research. In correlation research MoreThe purpose of this research is to investigate the impact of meta-heuristic hybrid algorithm analysis on portfolio diversification and excess returns of investment funds. In terms of method, the current research is a part of correlation research. In correlation research, the researcher's effort is focused on discovering or determining the relationship between one or more variables. In fact, the purpose of this method is to study the limits of changes of one or more variables with the limits of changes of one or more variables, and from the point of view of the purpose of this research, it is an applied research, the results of which can be useful for shareholders, stock exchange officials, and researchers. It is useful and in terms of the type of post-event studies that examines hypotheses based on past financial data. The statistical population of this research includes all the companies admitted to the Tehran Stock Exchange during the period of 36 months in the period from April 2019 to March 2011, which number is 591 companies based on the Rahevard software. According to the conditions and application of the aforementioned restrictions, 150 companies were selected as a sample in the 36 months ending in March 1401. By observing the results of the stock portfolio selection models with single and combined measures, we find that in all three models, the amount of risk increases with the increase in return. This shows that investors, in order to obtain more return, They are forced to accept Manuscript profile -
Open Access Article
9 - Presentation of algorithm for a full proximate flat surface optimum padding included obstacles with use routing algorithms
parisa padidar amirreza Estakhrian haghieghie -
Open Access Article
10 - A Simulated Annealing Algorithm within the Variable Neighbourhood Search Framework to Solve the Capacitated Facility Location-Allocation Problem
Ragheb Rahmaniani abdosalam Ghaderi Mohammad Saidi Mehrabad -
Open Access Article
11 - Optimization of Taleghan Dam Reservoir Operation Using Grey Wolf Algorithm and Its Hybrid with Genetic Algorithm
ardavan davani motlagh Mohammad Sadegh Sadeghian Amir Hossein Javid Mohammad Sadegh AsgariDue to population growth, shortage and severe limitation of water resources, one of the basic steps in water management and planning is reservoir optimization. In the present study, after the introduction of the Gray Wolf optimization algorithm, the performance of this MoreDue to population growth, shortage and severe limitation of water resources, one of the basic steps in water management and planning is reservoir optimization. In the present study, after the introduction of the Gray Wolf optimization algorithm, the performance of this algorithm alone and in combination with the genetic algorithm in optimizing the operation of the Taleghan Dam reservoir has been evaluated. The objective function is to minimize the total squares of relative deficiencies in allocating to it each month and maximize reliability throughout the 11-year transition period from 2009 to 2017. Also, the constraints of reservoir continuity equation, reservoir storage volume and reservoir release volume were applied to the objective function of the problem. The results obtained from the performance evaluation indices of the models showed that in terms of time reliability, vulnerability and sustainability indices, the gray wolf-genetic hybrid algorithm with 72.73, 0.28, 24.66 is better than the gray wolf algorithm with 68.93, 0.29, 21.48 and the algorithm. Genetics with 66.66, 0.41, 21.34. Manuscript profile -
Open Access Article
12 - A Hybrid Algorithm Based on Firefly Algorithm and Differential Evolution for Global Optimization
Sosan Sarbazfard Ahmad Jafarian -
Open Access Article
13 - Designing a New Structure Based on Learning Automaton to Improve Evolutionary Algorithms (With Considering Some Case Study Problems)
Ali Safari Mamaghani Kayvan Asghari Mohammad Reza Meybodi -
Open Access Article
14 - A Hybrid Approach for Content Replication Improvement in Content Delivery Networks
Mostafa Moradi -
Open Access Article
15 - A hybrid algorithm optimization approach for machine loading problem in flexible manufacturing system
Vijay M Kumar ANN Murthy K Chandrashekara -
Open Access Article
16 - Providing A New Characteristic for Overcurrent Relays
Keyvan Allahmoradi Mohsen Farshad Omid Bahrampour -
Open Access Article
17 - Determining optimal portfolio using fuzzy goal programing based on black hole and hybrid algorithms, considering investors preferences
Hamed Omidi hamedreza vakilifardThe variety of investment methods and the complexity of decision making has strongly developed in recent decades, and due to this widespread growth , there has been created need to inclusive and integrative models . to meet this need , financial modeling is MoreThe variety of investment methods and the complexity of decision making has strongly developed in recent decades, and due to this widespread growth , there has been created need to inclusive and integrative models . to meet this need , financial modeling is created from the connection between financial approach and mathematical planning.Assessing risk assets is one of the most important research issues in the financial field .There are various pricing models of capital assets in financial. In many models, it is not possible to consider a lot of restrictions on portfolio selection. In this paper, for choosing optimal portfolios, taking into account the prosperity and recession periods, and the types of investors in terms of risk taking and risk aversion as a limitation, fuzzy goal models(black hole algorithms ,hybrid algorithms and gravity) have been used. And finally, it has been compared to the results of the Markowitz pricing model. Manuscript profile
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