A Hybrid Approach Based on Immune Particle Swarm Optimization and Integer Liner Programming for the Container Loading Problem

This paper presents a novel hybrid approach for solving the Container Loading (CL) problem based on the combination of immune particle swarm optimization (IPSO) and Integer Linear Programming (ILP) model. More precisely, an IPSO engine works as a generator of reduced instances for the original CL problem, which are formulated as ILP models. These instances, in turn, are solved by ILP, and the performance measures accomplished by the respective models are interpreted as affinity values by the immune particle swarm optimization, thus guiding its evolutionary process. The proposed approach was compared with five well-known algorithms taken from the literature on the public benchmarks and the extensive computational results show that the quality of the solutions is equal to or better than that obtained by the best existing algorithms.