Hybrid ant colony optimization based on genetic algorithm for container loading problem

Abstract

A hybrid ant colony optimization based on Genetic Algorithm (GA) is applied to solving complex packing problem in the paper. Firstly, it searches for a set of rough solutions with the random search ability and the rapid global convergence of GA. Then, this set of solutions are used as the initial input of Ant Colony Optimization(ACO), using the positive feedback mechanism, the parallelism and the high efficiency of ACO to find the optimal solution of container loading problem. Finally, a design example is given in which 700 pieces of goods are loaded into a 40-foot container. The experimental results show that the hybrid algorithm can enhance the utilization of the container and it improves the performance of ACO and GA. © 2011 IEEE.