Hybrid ant colony optimization based on Genetic Algorithm for container loading problem

Author

Zhang, Dezhen ; Du, Lining

Author_Institution

Coll. of Comput. Sci. & Technol., Dalian Maritime Univ., Dalian, China

fYear

2011

fDate

14-16 Oct. 2011

Firstpage

10

Lastpage

14

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.

Keywords

ant colony optimisation; bin packing; computational complexity; genetic algorithms; complex packing problem; container loading problem; genetic algorithm; global convergence; hybrid ant colony optimization; positive feedback mechanism; random search ability; Algorithm design and analysis; Ant colony optimization; Containers; Genetic algorithms; Heuristic algorithms; Layout; Loading; ant colony optimization; container loading problem; dynamic integrates strategy; genetic algorithm; hybrid;

fLanguage

English

Publisher

ieee

Conference_Titel

Soft Computing and Pattern Recognition (SoCPaR), 2011 International Conference of

Conference_Location

Dalian

Print_ISBN

978-1-4577-1195-4

Type

conf

DOI

10.1109/SoCPaR.2011.6089106

Filename

6089106