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Multi-objective dynamic cell formation problem: A stochastic programming approach

Zohrevand, A. M ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1016/j.cie.2016.03.026
  3. Publisher: Elsevier Ltd
  4. Abstract:
  5. This paper addresses dynamic cell formation problem (DCFP) which has been explored vastly for several years. Although a considerable body of literature in this filed, two remarkable aspects have been significantly ignored so far, as uncertainty and human-related issues. In order to compensate such a shortage, this paper develops a bi-objective stochastic model. The first objective function of the developed model seeks to minimize total cost of machine procurement, machine relocation, inter-cell moves, overtime utilization, worker hiring/laying-off, and worker moves between cells; while the second objective function maximizes labor utilization of the cellular manufacturing system. In the developed model, labor utilization, worker overtime cost, worker hiring/laying off, and worker cell assignment are considered to tackle some of the most notable human-related issues in DCFP. Considering the complexity of the proposed model, a hybrid Tabu Search–Genetic Algorithm (TS–GA) is proposed whose strength is validated to obtain optimal and near optimal solutions through conducted experimental results
  6. Keywords:
  7. Cells ; Cytology ; Genetic algorithms ; Manufacture ; Multiobjective optimization ; Stochastic models ; Stochastic programming ; Stochastic systems ; Tabu search ; Dynamic cell formation ; Fuzzy sets theory ; Human-related issues ; Hybrid tabu search ; Inter-cell moves ; Labor utilization ; Near-optimal solutions ; Objective functions ; Cellular manufacturing
  8. Source: Computers and Industrial Engineering ; Volume 98 , 2016 , Pages 323-332 ; 03608352 (ISSN)
  9. URL: http://www.sciencedirect.com/science/article/pii/S0360835216300997