关键词: 多箱型三维装箱问题, 重力式空间搜索策略, 自适应算法, 粒子群算法, 动态编码

Abstract: To make the fast-economical box selection for e-commerce orders based on the Three-Dimensional Multiple Bin-Size Bin Packing Problem (3D-MBSBPP) model,the newspace search strategy and two algorithms were proposed.The self-adaptive stochastic algorithm realized the self-adaptation of cargo to space,and the cargo search rule realized the reasonable subdivision of cargo.The Particle Swarm Optimization (PSO) algorithm used dynamic coding,and implemented five types variation.To solve the existing three-dimensional packing cases,the space utilization rate was increased by 2.16%,which proved the effectiveness of the search strategy.The results of eight types of 3D-MBSBPP examples based on three-dimensional packing standard example were compared to the two algorithms.The adaptive random algorithm performed better on all examples,and the average gap value was better than the PSO by 19.59%.The superiority and stability of the adaptive random algorithm were proved.

Key words: three-dimensional multiple bin-size bin packing problem, gravity space search strategy, adaptive algorithm, particle swarm algorithm, dynamic coding