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Author: search.filters.author.Tarim, S. ArmaganSubject: search.filters.subject.Inventory

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  • Article
    Citation - WoS: 18
    Citation - Scopus: 23
    Computing Non-Stationary (S, S) Policies Using Mixed Integer Linear Programming
    (Elsevier Science Bv, 2018) Xiang, Mengyuan; Rossi, Roberto; Martin-Barragan, Belen; Tarim, S. Armagan
    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. (C) 2018 Elsevier B.V. All rights reserved.
  • Article
    Citation - WoS: 21
    Citation - Scopus: 24
    Heuristic Policies for the Stochastic Economic Lot Sizing Problem With Remanufacturing Under Service Level Constraints
    (Elsevier Science Bv, 2018) Kilic, Onur A.; Tunc, Huseyin; Tarim, S. Armagan
    In this paper, we address the stochastic economic lot sizing problem with remanufacturing under service level constraints. The problem emerges in hybrid production systems where demand can be met via two alternative sources: manufacturing new products and remanufacturing returned products. The deterministic counterpart of this problem has been considered in the literature and it is shown to be NP-Hard. We focus on the case where period demands and returns are stochastic. The optimal solution to this problem is not a deterministic production schedule but a control policy, yet its structure has not yet been characterized. We propose two heuristic policies for the problem that make use of simple decision rules to control manufacturing and remanufacturing operations and present mathematical models thereof. (C) 2018 Elsevier B.V. All rights reserved.