Multi Objective Hub LocationsProblem for Medical Supply ChainOptimization (Solving Sample Problems in Large Sizes with MOPSO and NSGA II Algorithms)

Abstract

Today, the problem of facility location planning is mainly from the long-term and strategic operational level of large private organizations. Based on the hub location model for the green supply chain of medical and pharmaceutical equipment, it is possible to investigate the current condition of the facilities and significantly improve the demand coverage by spending acceptable costs. Therefore, after presenting the mathematical model, validation was performed in small dimensions and then sensitivity analysis was performed on the main parameters of the model. Next, Bender's analysis algorithm was used to analyze the NP-hardness of the model. Finally, by comparing the model solving time without implementing the Benders decomposition algorithm and by using it, it is clear that in high-dimensional example problems, the Benders decomposition algorithm reaches the solution in much less time than the normal case, and according to the answers, the performance can be acceptable. In addition, to show the efficiency of the model, two meta-heuristic algorithms NSGAII and MOPSO were developed. Then, based on the analysis, it can be seen that the computational time increases exponentially with the increase in the size of the sample problems, which is a reason for the NP-Hard of the problem. However, the MOPSO algorithm is better than the NSGA II algorithm in terms of computational time up to medium size problems.