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

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