Multi-objective optimization of a stochastic assembly line balancing: A hybrid simulated annealing algorithm

作者：Cakir Burcin; Altiparmak Fulya^*; Dengiz Berna

来源：COMPUTERS & INDUSTRIAL ENGINEERING, 2011, 60(3): 376-384.

DOI：10.1016/j.cie.2010.08.013

• Stochastic assembly line balancing
• Parallel stations
• Multi-objective optimization
• Simulated annealing

This paper deals with multi-objective optimization of a single-model stochastic assembly line balancing problem with parallel stations. The objectives are as follows: (1) minimization of the smoothness index and (2) minimization of the design cost. To obtain Pareto-optimal solutions for the problem, we propose a new solution algorithm, based on simulated annealing (SA), called m_SAA, m_SAA implements a multinomial probability mass function approach, tabu list, repair algorithms and a diversification strategy. The effectiveness of m_SAA is investigated comparing its results with those obtained by another SA (using a weight-sum approach) on a suite of 24 test problems. Computational results show that m_SAA with a multinomial probability mass function approach is more effective than SA with weight-sum approach in terms of the quality of Pareto-optimal solutions. Moreover, we investigate the effects of properties (i.e., the tabu list, repair algorithms and diversification strategy) on the performance of m_SAA.

• 出版日期2011-4