Location optimization of logistics distribution centers based on improved salp swarm algorithm

Focusing on the multi-objective optimization models, in order to solve the location problem of logistics distribution centers more satisfactorily, we propose an improved multi-objective salp swarm algorithm (IMSSA). Based on the original salp swarm algorithm (SSA), the following improvement measures are put forward. Firstly, in order to be suitable for solving multi-objective problems, we introduce the concepts of non-dominated sorting, crowding distance and external archives to update basic SSA into multi-objective SSA. Then, a leader position update strategy is adopted based on the idea of evolutionary game theory. In addition, simulated annealing mechanism is applied to improve the position update strategy of followers. Finally, the proposed IMSSA is employed to optimize the location of distribution centers of a bidirectional two-tier logistics network, and the comparative analysis of the Pareto solution sets verifies the feasibility and effectiveness of the proposed algorithm.