Improvement Grouping Genetic Algorithm for Solving the Bin Packing Problem

Abstract

Abstract An improved grouping genetic algorithm is proposed to solve the one-dimensional bin packing problem. In this algorithm, a new crossover operator is constructed according to the characteristics of the encoding. At the same time, a replacement insertion method is designed to improve the mutation operation. The new mutation operation prevents the algorithm from falling into a local optimum and improves the transmission speed of the best individual in the chromosome. The analysis and comparison of experimental results show that the proposed algorithm can effectively solve the one-dimensional bin packing problem and has reliable global convergence.