Endüstri Mühendisliği Bölümü Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.11779/1942

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    Book Part
    Citation - WoS: 12
    Citation - Scopus: 12
    Bilevel Models on the Competitive Facility Location Problem
    (Springer, 2017) Küçükaydın, Hande; Aras, Necati; 02.01. Department of Industrial Engineering; 02. Faculty of Engineering; 01. MEF University
    Facility location and allocation problems have been a major area of research for decades, which has led to a vast and still growing literature. Although there are many variants of these problems, there exist two common features: finding the best locations for one or more facilities and allocating demand points to these facilities. A considerable number of studies assume a monopolistic viewpoint and formulate a mathematical model to optimize an objective function of a single decision maker. In contrast, competitive facility location (CFL) problem is based on the premise that there exist competition in the market among different firms. When one of the competing firms acts as the leader and the other firm, called the follower, reacts to the decision of the leader, a sequential-entry CFL problem is obtained, which gives rise to a Stackelberg type of game between two players. A successful and widely applied framework to formulate this type of CFL problems is bilevel programming (BP). In this chapter, the literature on BP models for CFL problems is reviewed, existing works are categorized with respect to defined criteria, and information is provided for each work.
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    Article
    Citation - WoS: 5
    Citation - Scopus: 6
    Generation of Feasible Integer Solutions on a Massively Parallel Computer Using the Feasibility Pump
    (2017) Mehrotra, Sanjay; Koç, Utku; 02.01. Department of Industrial Engineering; 02. Faculty of Engineering; 01. MEF University
    We present an approach to parallelize generation of feasible mixed integer solutions of mixed integer linear programs in distributed memory high performance computing environments. This approach combines a parallel framework with feasibility pump (FP) as the rounding heuristic. It runs multiple FP instances with different starting solutions concurrently, while allowing them to share information. Our computational results suggest that the improvement resulting from parallelization using our approach is statistically significant. (C) 2017 Elsevier B.V. All rights reserved.