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1 - meta-heuristic algorithms to solve the problem of terminal facilities on a real scale
مهدی فضلی فرزین مدرس خیابانی بهروز دانشیان

a b s t r a c tOur main goal in this article is to arrange terminal facilities, place different departments, stores and units in predefined areas in such a way as to minimize the cost of moving customers and transportation staff. Especially in large-scale terminals with More

a b s t r a c tOur main goal in this article is to arrange terminal facilities, place different departments, stores and units in predefined areas in such a way as to minimize the cost of moving customers and transportation staff. Especially in large-scale terminals with several different transport segments, it is important for terminal performance to be close to interactive units. Today, meta-heuristic methods are often used to solve optimization problems such as facility design. in this study; The design of the various units, stores, and rooms of a large-scale real terminal was organized using three meta-heuristic algorithms: Migratory Bird Optimization (MBO), Taboo Search (TS), and Simulated Simulation (SA). The results were compared with the existing terminal design. As a result, MBO and SA metaheuristic algorithms have provided the best results, which improve the efficiency of the existing terminal design to an acceptable level. Manuscript profile
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2 - Use whale algorithm and neighborhood search metaheuristics with fuzzy values to solve the location problem
مهدی فضلی فرزین مدرس خیابانی بهروز دانشیان
20.1001.1.25885723.2021.13.3.3.0

In this paper, a facility location model with fuzzy value parameters based on the meta-heuristic method is investigated and solved. The proposed method and model uses fuzzy values to investigate and solve the problem of location allocation. The hypotheses of the problem More

In this paper, a facility location model with fuzzy value parameters based on the meta-heuristic method is investigated and solved. The proposed method and model uses fuzzy values to investigate and solve the problem of location allocation. The hypotheses of the problem in question are considered as fuzzy random variables and the capacity of each facility is assumed to be unlimited. This article covers a modern, nature-inspired method called the whale algorithm and the neighborhood search method. The proposed method and related algorithm are tested with practical optimization problems and modeling problems. To evaluate the efficiency and performance of the proposed method, we apply this method to our location models in which fuzzy coefficients are used. The results of numerical optimization show that the proposed method performs better than conventional methods. Manuscript profile
Open Access Article
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3 - A new method for solving of the Graph Coloring Problem based on a fuzzy logic and whale optimization algorithm
طاها مصطفایی فرزین مدرس خیابانی نیما جعفری نویمی پور بهروز دانشیان
20.1001.1.25885723.2021.13.2.2.7

Abstract: In recent years, Graph Coloring Problem (GCP) is one of the main optimization problems from literature. Many real world problems interacting with changing environments can be modeled by dynamic graphs. Graph vertex coloring with a given number of colors is a w More

Abstract: In recent years, Graph Coloring Problem (GCP) is one of the main optimization problems from literature. Many real world problems interacting with changing environments can be modeled by dynamic graphs. Graph vertex coloring with a given number of colors is a well-known and much-studied NP-hard problem. Meta-heuristic algorithms are a good choice to solve GCP because they are suitable for problems with NP-hard complexity. However, in many previously proposed algorithms, there are common problems such as runtime algorithm and low convergence of algorithm. Therefore, in this paper, we propose the Fuzzy Whale Optimization Algorithm (FWOA), a variety of basic Whale Optimization Algorithm (WOA), to improve runtime and convergence of algorithm in the GCP. Since WOA at first was introduced for solving continuous problem, we need a discrete WOA. Hence, to use FWOA to discrete search space, the standard arithmetic operators such as addition, subtraction and multiplication extant in FWOA encircling prey, exploitation phase and exploration phase operators based on distance’s theory needs to be redefined in the discrete space. Parameters p and r, are defined randomly in the WOA algorithm in FWOA algorithm defined as fuzzy and are selected in fuzzy tragedy. A set of graph coloring benchmark problems are solved and their performance are compared with some well-known heuristic search methods. Results illustrate that FWOA algorithm are the original focus of this work and in most cases success rate is nearly 100% and the runtime and convergence algorithm has been improved on some graphs. But as we have illustrated that comparison with other manners, we cannot deduce that our algorithm is the best in all instance of graphs. It can be said that a proposed algorithm is able to compete with other algorithms in this context. Obtained results approved the high performance of proposed method. Manuscript profile

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