 A combinatorial optimisation approach for closed-loop supply chain inventory planning with deterministic demandPierre Desport, Frédéric Lardeux, David Lesaint, Carla Di Cairano-Gilfedder, Anne Liret and Gilbert Owusu European Journal of Industrial Engineering, 2017, vol. 11, issue 3, 303-327 Abstract: Supply chains in equipment-intensive service industries often involve repair operations. In this context, tactical inventory planning is concerned with optimally planning supplies and repairs based on demand forecasts and in the face of conflicting business objectives. This paper considers closed-loop supply chains and proposes a mixed-integer programming model and a metaheuristic approach to this problem. The model is open to a variety of network topologies, site functions and transfer policies. It also accommodates multiple objectives by the means of a weighted cost function. We report experiments on pseudo-random instances designed to evaluate plan quality and impact of cost weightings. In particular, we show how appropriate weightings allow to implement common planning strategies (e.g., just-in-time replenishment, minimal repair). [Received 8 May 2016; Revised 24 October 2016; Accepted 2 December 2016] Keywords: supply chain planning; planning strategies; mixed integer programming; metaheuristics; closed-loop. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:eujine:v:11:y:2017:i:3:p:303-327 Access Statistics for this article More articles in European Journal of Industrial Engineering from Inderscience Enterprises Ltd |
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