Optimization model of portable cross-dock using genetic and Grey Wolf algorithm

Warehousing using cross-docking is a well-known approach to distribute the products and decrease the costs of inventories and logistics in supply chain. In a cross-docking system, the goods are delivered from the delivery loader and move directly to the shipping loader without storage in the warehouse or distribution center. The use of this system reduces manpower costs, inventory, as well as increasing customer response speed and better control of distribution operations. However, in this research, the plan of portable cross warehouse along with the use of fixed cross warehouse in order to reduce the costs of constructing a cross warehouse has been proposed. Therefore, by presenting a random mathematical model, it has been tried to determine the appropriate place to send and establish a portable and fixed cross warehouse, as well as planning to determine which type of warehouse to be used in each location, transportation costs. To minimize possible and due to the uncertainty of the amount of demand for goods to be transferred between the pickup and Delivery points, the fuzzy programming method has been used. Genetic and Gray Wolf Optimizer have been used to solve the proposed model. To validate the performance of these evolutionary algorithms, for small-scale problems, it is used the solvers of GAMS software. The results of optimization show that the grey wolf algorithm provides better performance from the aspect of running time and the value of objective function. The number of products sent to the portable cross dock is one of the main results of this research.