Volume 27, Issue 2 (IJIEPR 2016)                   IJIEPR 2016, 27(2): 121-139 | Back to browse issues page

DOI: 10.22068/ijiepr.27.2.121


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1- Bu-Ali Sina University , fattahi@basu.ac.ir
2- Bu-Ali Sina University
Abstract:   (3994 Views)

In this paper, a stochastic cell formation problem is studied using queuing theory framework and considering reliability. Since cell formation problem is NP-Hard, two algorithms based on genetic and modified particle swarm optimization (MPSO) algorithms are developed to solve the problem. For generating initial solutions in these algorithms, a new heuristic method is developed, which always creates feasible solutions. Moreover, full factorial and Taguchi methods are implemented to set crucial parameters in the solutions procedures. Deterministic method of branch and bound (B&B) algorithm is used to evaluate the results of modified particle swarm optimization algorithm and the genetic algorithm. The results indicate that proposed algorithms have better performance in quality of the metaheurstic algorithms final answer and solving time compared with the method of Lingo software’s B&B algorithm. The solution of two metaheurstic algorithms is compared by t test. Ultimately, the results of numerical examples indicate that considering reliability has significant effect on block structures of machine-part matrixes.

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Type of Study: Research | Subject: Facilities Planning and Management
Received: 2015/12/20 | Accepted: 2016/12/3 | Published: 2016/12/6