A particle swarm optimization for solving the one dimensional container loading problem

Abstract

We address in this paper the one dimensional container loading problem (CLP), a NP-hard optimization problem of extreme economic relevance in industrial areas. The problem consists in loading items into containers, then stowing the most profitable containers in a set of compartments. The main objective is to minimize the number of used containers. We state a mathematical model as well as a modified metaheuristic namely the particle swarm optimization approach (PSO) with FFD initialization. Computational results carried out on a large test bed show the effectiveness of the denoted approach depending on the problem settings.