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

被引:120
作者
Yagmahan, Betul [1 ]
机构
[1] Uludag Univ, Fac Engn & Architecture, Dept Ind Engn, TR-16059 Bursa, Turkey
关键词
Assembly line balancing; Mixed-model; Ant colony optimization; Multi-objective; FORMULATION; ALGORITHM; SYSTEM;
D O I
10.1016/j.eswa.2011.04.026
中图分类号
TP18 [人工智能理论];
学科分类号
140502 [人工智能];
摘要
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. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:12453 / 12461
页数:9
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