Mixed-model assembly line balancing using a multi-objective ant colony optimization approach

Authors:
Betul Yagmahan
Affiliations:
Department of Industrial Engineering, Faculty of Engineering and Architecture, Uludag University, Gorukle Campus, Bursa 16059, Turkey
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

Citing 5
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Abstract

Mixed-model assembly lines are production systems at which two or more models are assembled sequentially at the same line. For optimal productivity and efficiency, during the design of these lines, the work to be done at stations must be well balanced satisfying the constraints such as time, space and location. This paper deals with the mixed-model assembly line balancing problem (MALBP). The most common objective for this problem is to minimize the number of stations for a given cycle time. However, the problem of capacity utilization and the discrepancies among station times due to operation time variations are of design concerns together with the number of stations, the line efficiency and the smooth production. A multi-objective ant colony optimization (MOACO) algorithm is proposed here to solve this problem. To prove the efficiency of the proposed algorithm, a number of test problems are solved. The results show that the MOACO algorithm is an efficient and effective algorithm which gives better results than other methods compared.