Two-stage flow distribution model based on multi-objective optimization

Abstract

Efficiency and effectiveness of the logistics network is directly dependent on network topology and flow distribution of logistics nodes and transport routes. Flow distribution model based on multi-objective function belongs to NP-difficult problem. The model consists of supply, demand and constraints of network capacity and so on. The number of network paths will exponentially expand with the size of the network, that is, when the number of various types of nodes increases, the overall transportation route will rapidly increase. So we design a “sliced, two-phase” flow distribution model of logistics network. Combining with penalty-parameter-less method, we use particle swarm optimization (PSO) algorithm to optimize the model so as to find the solution of multi-objective function. Experiment results show that PSO algorithm with penalty function method can obtain satisfactory solution of flow distribution and network usage in a short period of time.