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Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/403
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Article Citation - WoS: 18Citation - Scopus: 23Computing Non-Stationary (S, S) Policies Using Mixed Integer Linear Programming(Elsevier Science Bv, 2018) Xiang, Mengyuan; Rossi, Roberto; Martin-Barragan, Belen; Tarim, S. ArmaganThis 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: 21Citation - Scopus: 24Heuristic 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. ArmaganIn 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.Article Citation - WoS: 9Citation - Scopus: 11Confidence-Based Reasoning in Stochastic Constraint Programming(Elsevier, 2015) Rossi, Roberto; Hnich, Brahim; Tarim, S. Armagan; Prestvvich, Steven; Prestwich, StevenIn this work we introduce a novel approach, based on sampling, for finding assignments that are likely to be solutions to stochastic constraint satisfaction problems and constraint optimisation problems. Our approach reduces the size of the original problem being analysed; by solving this reduced problem, with a given confidence probability, we obtain assignments that satisfy the chance constraints in the original model within prescribed error tolerance thresholds. To achieve this, we blend concepts from stochastic constraint programming and statistics. We discuss both exact and approximate variants of our method. The framework we introduce can be immediately employed in concert with existing approaches for solving stochastic constraint programs. A thorough computational study on a number of stochastic combinatorial optimisation problems demonstrates the effectiveness of our approach. (C) 2015 Elsevier B.V. All rights reserved.Article Citation - WoS: 97Citation - Scopus: 119The Degree of Financial Liberalization and Aggregated Stock-Return Volatility in Emerging Markets(Elsevier Science Bv, 2010) Akdeniz, Levent; Altay-Salih, Aslihan; Umutlu, MehmetIn this study, we address whether the degree of financial liberalization affects the aggregated total volatility of stock returns by considering the time-varying nature of financial liberalization. We also explore channels through which the degree of financial liberalization impacts aggregated total volatility. We document a negative relation to the degree of financial liberalization after controlling for size, liquidity, country. and crisis effects, especially for small and medium-sized markets. Moreover, the degree of financial liberalization transmits its negative impact on aggregated total volatility through aggregated idiosyncratic and local volatilities. Overall, our results provide evidence in favor of the view that the broadening of the investor base due to the increasing degree of financial liberalization causes a reduction in the total volatility of stock returns. (C) 2009 Elsevier B.V. All rights reserved.