A robust optimisation model for manufacturing cell design problem under uncertainty

Majid Soolaki and Alireza Izadi

International Journal of Services and Operations Management, 2013, vol. 15, issue 2, 238-258

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.

Keywords: robust optimisation; dynamic CMS; cellular manufacturing systems; DCMS; uncertainty; mixed-integer linear programming; MILP; modelling; manufacturing cells; cell design; cell formation. (search for similar items in EconPapers)
Date: 2013
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