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

Document Type: Original Manuscript

Authors

1 Associate Professor, Department of Industrial Engineering, Alzahra University, Tehran, Iran

2 MSc, Department of Industrial Engineering, Bu-Ali Sina University, Hamedan, Iran

Abstract

In today’s competitive market, those producers who can quickly adapt themselves todiverse demands of customers are successful. Therefore, in order to satisfy these demands of market, Mixed-model assembly line (MMAL) has an increasing growth in industry. A mixed-model assembly line (MMAL) is a type of production line in which varieties of products with common base characteristics are assembled on. This paper focuses on this type of production line in a stochastic environment with three objective functions: 1) total utility work cost, 2) total idle cost, and 3) total production rate variation cost that are simultaneously considered.
 In real life, especially in manual assembly lines, because of some inevitable human mistakes, breakdown of machines, lack of motivation in workers and the things alike, events are notdeterministic, sowe consideroperation time as a stochastic variable independently distributed with normal distributions; for dealing with it, chance constraint optimization is used to model the problem. At first, because of NP-hard nature of the problem, multi-objective harmony search (MOHS) algorithm is proposed to solve it. Then, for evaluating the performance of the proposed algorithm, it is compared with NSGA-II that is a powerful and famous algorithm in this area. At last, numerical examples for comparing these two algorithms with some comparing metrics are presented. The results have shown that MOHS algorithm has a good performance in our proposed model.

Highlights

  • A mixed-model assembly line (MMAL) is a type of production line in which a variety of products with common base characteristics are assembled on.
  • This paper focuses on this type of production line in a stochastic environment with three objective functions: 1) total utility work cost, 2) total idle cost, and 3) total production rate variation cost that are simultaneously considered.
  • At first, Chance constraint optimization is used to model the problem, then because of NP-hardness nature of problem the Multi-Objective Harmony Search (MOHS) algorithm is proposed to solve it.
  • Then for evaluating the performance of proposed algorithm, it is compared with NSGA-II that is a powerful and famous algorithm in this area.

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Main Subjects