A parallel multiple Markov chain simulated annealing for multi-period manufacturing cell formation problems

Abstract

Simulated annealing (SA) is a general purpose optimization technique capable of finding optimal or near optimal solutions in various applications. The major disadvantage of this technique is its slow convergence making it not suitable for solving many complex optimization problems. This limitation may be alleviated by parallel computing using a multiprocessor computer or a cluster of workstations. In this paper, we present an integer programming model for solving a multi-period cell formation problem in cellular manufacturing system. In order to solve the mathematical model efficiently, we developed a multiple Markov chain simulated annealing algorithm which allows multiple search directions to be traced simultaneously. Our computational results on a single processor machine showed that multiple Markov chain SA is much more efficient than a conventional single Markov chain SA. The parallel implementation of the multiple Markov chain SA further improves its computational efficiency in terms of solution quality and execution time.