Hybrid Particle Swarm Optimization Algorithm for the Logistics Network Design Problem under Concave Cost Function

An effective hybrid algorithm integrated the heuristic route exploration algorithm (HRE) and particle swarm optimization (PSO) is proposed for logistics network design problem with transportation concave cost function between plants and distribution centers. In this solution, PSO is used to search feasible logistics network structures, while HRE algorithm is used to decide whether to route a shipment through an intermediate consolidation centers or route it directly to its distribution centers. A novel encoding scheme satisfying spontaneously with complicated constraints is designed. Two particle state updating mechanisms are presented to mitigate premature convergence. Simulation results and comparisons demonstrate the effectiveness of the proposed hybrid PSO algorithm.