A Multi-Objective Mixed-Model Assembly Line Sequencing Problem with Stochastic Operation Time

In today’s competitive market, those producers who can quickly adapt themselves to diverse demands of customers are successful. Therefore, inorder to satisfy these demands of market, Mixed-model assembly line (MMAL) has an increasing growth in industry. A mixed-model assemblyline (MMAL) is a type of production line in which varieties of products with common base characteristics are assembled on. This paper focuseson this type of production line in a stochastic environment with three objective functions: 1) total utility work cost, 2) total idle cost, and 3) totalproduction rate variation cost that are simultaneously considered.In real life, especially in manual assembly lines, because of some inevitablehuman mistakes, breakdown of machines, lack of motivation in workers and the things alike, events are not deterministic, so weconsideroperation time as a stochastic variable independently distributed with normal distributions; for dealing with it, chance constraint optimization isused to model the problem. At first, because of NP-hard nature of the problem, multi-objective harmony search (MOHS) algorithm is proposedto solve it. Then, for evaluating the performance of the proposed algorithm, it is compared with NSGA-II that is a powerful and famousalgorithm in this area. At last, numerical examples for comparing these two algorithms with some comparing metrics are presented. The resultshave shown that MOHS algorithm has a good performance in our proposed model.

Keywords:

Mixed-model assembly line sequencing , Stochastic operation time , Chance constraint