Browsing by Subject "Linear programming models"

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    Hub location under competition
    (Elsevier, 2016) Mahmutogullari, A. I.; Kara, B. Y.
    Hubs are consolidation and dissemination points in many-to-many flow networks. Hub location problem is to locate hubs among available nodes and allocate non-hub nodes to these hubs. The mainstream hub location studies focus on optimal decisions of one decision-maker with respect to some objective(s) even though the markets that benefit hubbing are oligopolies. Therefore, in this paper, we propose a competitive hub location problem where the market is assumed to be a duopoly. Two decision-makers (or firms) sequentially decide locations of their hubs and then customers choose one firm with respect to provided service levels. Each decision-maker aims to maximize his/her own market share. We propose two problems for the leader (former decision-maker) and follower (latter decision-maker): (r|Xp)hub − medianoid and (r|p)hub − centroid problems, respectively. Both problems are proven to be NP-complete. Linear programming models are presented for these problems as well as exact solution algorithms for the (r|p)hub − centroid problem. The performance of models and algorithms are tested by computational analysis conducted on CAB and TR data sets.
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    Incorporating just-in-time into a decision support system environment
    (Elsevier BV, 1991) Oǧuz, Ceyda; Dinçer, Cemal
    In this paper, a Decision Support System is proposed for a Just-In-Time production system. The Decision Support System includes three components: database, model base, and interface. The database contains the predefined parameters together with the data generated for the considered Just-In-Time production system. In the model base, both deterministic and stochastic aspects of the system are considered. The deterministic system is examined by constructing a linear programming model whereas simulation is used as a tool for the stochastic system. Furthermore, a sensitivity analysis is performed on the Just-In-Time production system with the help of the Decision Support System environment for the unit load size changes under different demand patterns by using the alternative solutions obtained from the model base.