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A robust optimisation model for manufacturing cell design problem under uncertainty

Author

Listed:
  • Majid Soolaki
  • Alireza Izadi

Abstract

The concern about significant changes in the manufacturing environment (such as operating/part costs and part demands) has spurred an interest in designing robust dynamic cellular manufacturing systems (RDCMS). Here, first a deterministic mixed-integer linear programming (MILP) model for cell formation is proposed. Cost parameters of model and demand fluctuations are subject to uncertainty. The objective function calculates machine costs, operating cost, internal part production cost, inter-cellular material handling cost, backorder cost, inventory holding cost and subcontracting. Then the robust counterpart of the proposed mixed integer linear programming model is presented by using the recent extensions in robust optimisation theory. Finally, to assess the robustness of the solutions obtained by the novel robust optimisation model, they are compared to those generated by the deterministic mixed-integer linear programming model in a number of realisations under different test problems. Numerical tests show the power of the proposed robust model in handling uncertainty in parameters and generating robust optimal solutions.

Suggested Citation

  • Majid Soolaki & Alireza Izadi, 2013. "A robust optimisation model for manufacturing cell design problem under uncertainty," International Journal of Services and Operations Management, Inderscience Enterprises Ltd, vol. 15(2), pages 238-258.
    • Handle: RePEc:ids:ijsoma:v:15:y:2013:i:2:p:238-258
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