Multi-objective Ant Colony Optimization Method to Solve Container Terminal Problem

Abstract

The river and maritime transport represents an attractive alternative to land and air transport. The containerization allows the industries to save costs thanks to the standardization of dimensions. The container terminal has to manage container traffic at the crossroads of land road and railway. In this chapter, we propose to optimize, simultaneously, the storage problem and the quayside transport problem. In a space storage, we have several blocks and each one has its storage cost. The first aim is to minimize the cost storage of containers. These latter are loaded into vessels, the vehicles have to transport the containers from blocks to quays (of vessels). Thus, the second aim consists to minimize the distance between the space storage and the quays. The optimization methods of operations research in container terminal operation have become more and more important in recent years. Objective methods are necessary to support decisions. To solve this multi-objective problem, we develop two resolution methods based on metaheuristic approach called ant colony algorithm. The first one is multi-objective ant colony optimization (noted MOACO) and the second one is the MOACO with a local search (called MOACO-LS), good promising results are given.