Computing non-stationary (s, S) policies using mixed integer linear programming

Xiang M., Rossi R., Martin-Barragan B., TARIM Ş. A.

European Journal of Operational Research, vol.271, no.2, pp.490-500, 2018 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 271 Issue: 2
  • Publication Date: 2018
  • Doi Number: 10.1016/j.ejor.2018.05.030
  • Journal Name: European Journal of Operational Research
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.490-500
  • Keywords: (s, S) policy, Binary search, Inventory, Mixed integer programming, Stochastic lot-sizing
  • Hacettepe University Affiliated: Yes

Abstract

This paper addresses the single-item single-stocking location non-stationary stochastic lot sizing problem under the (s, S) control policy. We first present a mixed integer non-linear programming (MINLP) formulation for determining near-optimal (s, S) policy parameters. To tackle larger instances, we then combine the previously introduced MINLP model and a binary search approach. These models can be reformulated as mixed integer linear programming (MILP) models which can be easily implemented and solved by using off-the-shelf optimization software. Computational experiments demonstrate that optimality gaps of these models are less than 0.3% of the optimal policy cost and computational times are reasonable.