Hub location in multi-modal green air transportation supporting network using Genetic Algorithm

Green air transportation supporting network consists of demand and demand satisfaction by environmental goals. In this article we seek to create a green supporting network in air industries in a way that the centers of pollutants are avoided to be installed in polluted areas as much as possible. Centralization causes optimal use of transportation facilities and finally reduces the pollution. A multi-modal transportation supporting network can play an important role by optimal hub location, considering network goals such as minimizing environmental pollution. In this paper, by considering the time scheduled for delivery of each part to air stations, an optimum mathematical model is presented. Multi-modal transportation is one of the innovations of this paper which is created by planning a comprehensive and flexible model in transportation. Due to the uncertain nature of many factors in real-world problems, transportation time parameter is considered to be fuzzy. Jimenez approach is applied to transform the fuzzy model to crisp one. The model is solved and validated after linearization by GAMS software and CPLEX solver. The meta-heuristic Genetic Algorithm method is used for solving the model in large-scales. The Genetic Algorithm detects and displays the optimal situation with an acceptable error.