Title: A combinatorial optimisation approach for closed-loop supply chain inventory planning with deterministic demand
Authors: Pierre Desport; Frédéric Lardeux; David Lesaint; Carla Di Cairano-Gilfedder; Anne Liret; Gilbert Owusu
Addresses: LERIA, Universite d'Angers, 2 Boulevard de Lavoisier, 49045 Angers, France ' LERIA, Universite d'Angers, 2 Boulevard de Lavoisier, 49045 Angers, France ' LERIA, Universite d'Angers, 2 Boulevard de Lavoisier, 49045 Angers, France ' BT, Adastral Park, Martlesham Heath IP5 3RE, UK ' BT France, 92088 Paris La Defense Cedex, France ' BT, Adastral Park, Martlesham Heath IP5 3RE, UK
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.
European Journal of Industrial Engineering, 2017 Vol.11 No.3, pp.303 - 327
Available online: 01 Jul 2017 *Full-text access for editors Access for subscribers Purchase this article Comment on this article