Optimizing a multi-stage production/inventory system by DC programming based approaches

Hoai Le Thi () and Duc Tran ()

Computational Optimization and Applications, 2014, vol. 57, issue 2, 468 pages

Abstract: This paper deals with optimizing the cost of set up, transportation and inventory of a multi-stage production system in presence of bottleneck. The considered optimization model is a mixed integer nonlinear program. We propose two methods based on DC (Difference of Convex) programming and DCA (DC Algorithm)—an innovative approach in nonconvex programming framework. The mixed integer nonlinear problem is first reformulated as a DC program and then DCA is developed to solve the resulting problem. In order to globally solve the problem, we combine DCA with a Branch and Bound algorithm (BB-DCA). A convex minorant of the objective function is introduced. DCA is used to compute upper bounds while lower bounds are calculated from a convex relaxation problem. The numerical results compared with those of COUENNE ( http://www.coin-or.org/download/binary/Couenne/ ), a solver for mixed integer nonconvex programming, show the rapidity and the ϵ-globality of DCA in almost cases, as well as the efficiency of the combined DCA-Branch and Bound algorithm. We also propose a simple heuristic algorithm which is proved by experimental results to be better than an existing heuristic in the literature for this problem. Copyright Springer Science+Business Media New York 2014

Keywords: Mixed integer nonlinear program; DC programming; DCA; Branch and bound; Multistage manufacturing system; Lot size; Unequal batches (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10589-013-9600-5

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