Browsing by Author "Ozpeynirci, Selin"

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A Branch-And Approach for Computing the Minimum Number of Pairwise Comparisons in Multicriteria Selection Based on Convex Cones
(Pergamon-Elsevier Science Ltd, 2026) Ozpeynirci, Ozgur; Ozpeynirci, Selin
We study the multiple criteria selection problem (MCSP), where the aim is to identify the most preferred alternative among a set of known alternatives evaluated on multiple criteria. While several methods have been developed for MCSP, which utilize pairwise comparisons, it remains unknown how close these approaches are to the theoretical minimum number of pairwise comparisons required. To address this gap, we propose a computational framework that determines the theoretical lower bound on the number of pairwise comparisons required under the assumption that the DM's value function is known. Although this assumption is not realistic for real-world decision support, it is essential for establishing a rigorous performance standard against which algorithms can be evaluated. While this framework provides a basis for benchmarking interactive algorithms, its applicability is specific to pairwise comparison procedures that utilize convex cones. The benchmark is formulated as a large-scale integer programming problem and solved via a branch-and-price approach, where column generation is used to generate only the most promising convex cones. We further extend the model to incorporate transitivity, which can reduce the number of comparisons but increases computational effort. Extensive computational experiments are conducted across diverse problem instances. Beyond providing benchmark values, the results reveal structural patterns-such as when the optimal solution relies primarily on 2-point or 3-point cones, and when higher-level cones are required. These insights not only strengthen the role of the benchmark as a theoretical reference, but also offer practical guidance for designing more efficient algorithms for MCSP.
Cooperative Scheduling and Subcontracting Strategies for Products with Yield Decay: A Mixed-Integer Programming Approach
(Pergamon-Elsevier Science Ltd, 2026) Gokgur, Burak; Ozpeynirci, Selin; Tanil, Mutlu Ipek
This study introduces a mixed-integer programming framework to analyze cooperative scheduling and outsourcing decisions for perishable products affected by yield decay. We study two manufacturers that share a subcontractor, operate under sequence-dependent setup times, and aim to schedule their operations to maximize profit. Three subcontracting strategies are assessed: no subcontracting, non-cooperative subcontracting, and cooperative scheduling. Our illustrative example and extensive numerical experiments across 18 scenarios demonstrate notable efficiency gains. Cooperation improves total supply chain profit by 4.55 % under low setup times and up to 147.37 % under high setup times. Changes in subcontractor costs cause asymmetric profit redistributions, with decreases of 19.6 % for the lead firm and increases of 47.4 % for the follower in the Principal-Agent framework. When tardiness penalties are high, cooperation improves profit by 30.2 % compared to non-cooperation. A probabilistic analysis of subcontractor access indicates that total supply chain profit peaks when the follower has priority, despite this conflicting with individual firm incentives. Conditional Value-at-Risk analysis emphasizes the asymmetric downside risks of decentralization, with one firm being more vulnerable in worst-case scenarios. Overall, these findings highlight the benefits of cooperative subcontracting and underscore the importance of incentive-compatible contracts and risk-sharing mechanisms in shared-capacity environments with time-sensitive yield decay.