Pool-based Evolutionary Algorithm for the Bin Packing Problem

Abstract

Bin packing problem is one of the most important optimization problems from the literature. In this work, we propose a novel pool-based evolutionary algorithm for solving the one-dimensional bin packing problem. The algorithm exploits a pool-based crossover operator that aims to increase the search space of the problem and combine and remap as a local search technique that aims to improve the quality of the solution by considering underutilized bins in the offspring. The proposed method is applied to medium and hard instances taken from benchmark problem sets and is compared with six algorithms from the literature. Our experimental evolution indicates that the proposed algorithm outperforms these algorithms in most of the test cases provided.