Multi-rule multi-objective Ant Colony Optimization for straight and U-type assembly line balancing problem

Author

Khaw, Christopher L E ; Ponnambalam, S.G.

Author_Institution

Monash Univ., Bandar, Malaysia

fYear

2009

fDate

22-25 Aug. 2009

Firstpage

177

Lastpage

182

Abstract

In this paper, a hybrid algorithm by combining 15 task assignment rules and ant colony optimization (ACO) algorithm to solve straight and U-type assembly line balancing problem to optimize line efficiency and smoothness index is proposed. The algorithm is designed to solve assembly line balancing problems of all sizes. The proposed multi-rule multiobjective ant colony optimization algorithm for straight and U-type assembly line balancing problems is evaluated with various set of benchmark problems and compared with a multi-objective simulated annealing algorithm reported in the literature. The results indicate the better performance of the proposed hybrid algorithm.

Keywords

assembling; optimisation; U-type assembly line balancing problem; hybrid algorithm; multiobjective simulated annealing; multirule multiobjective ant colony optimization; straight assembly line balancing problem; task assignment rule; Algorithm design and analysis; Ant colony optimization; Assembly; Automation; Industrial engineering; Production systems; Simulated annealing; Topology; Toy manufacturing industry; Workstations;

fLanguage

English

Publisher

ieee

Conference_Titel

Automation Science and Engineering, 2009. CASE 2009. IEEE International Conference on

Conference_Location

Bangalore

Print_ISBN

978-1-4244-4578-3

Electronic_ISBN

978-1-4244-4579-0

Type

conf

DOI

10.1109/COASE.2009.5234122

Filename

5234122