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2011 - 20182
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Yazar: Atan, Sabri Tankut × WoS Q: Q1 ×

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  • Küçük Resim
    Yayın
    Optimal project duration for resource leveling
    (Elsevier Science BV, 2018-04-16) Atan, Sabri Tankut; Eren, Elif
    Resource leveling is important in project management as resource fluctuations are costly and undesired. Typically, schedules with better resource profiles are obtained by shifting the activities within their float times using the schedule of fixed duration found by Critical Path Method. However, if the project duration can be extended, it is plausible to find a schedule with enhanced resource leveling since a longer duration allows for more float time for all activities. In this work, we relax the assumption of fixed durations in resource leveling formulations and investigate what the minimal project duration for the best leveled schedule should be. We provide mixed-integer linear models for several leveling objectives including the Release and Rehire metric. We show that not all metrics used for leveling under fixed durations may be appropriate when the project duration becomes a decision variable. Optimal solutions from smaller problems are used to find the magnitude of the extension needed and benefits obtained thereby. Since the problem is a NP-hard problem for which exact solutions cannot be obtained for large networks in reasonable time, we provide a greedy heuristic to be used with the Release and Rehire metric. Using an iterative framework, we also test the performance of a state-of-the-art heuristic algorithm from the literature on our problem. Computational experiments indicate that the more the number of resources is increased, the less leveling benefits are gained from extending the project. The optimal project durations and extension benefits can also be significantly different for different metrics.
  • Küçük Resim
    Yayın
    Re-mining item associations: Methodology and a case study in apparel retailing
    (Elsevier Science BV, 2011-12) Demiriz, Ayhan; Ertek, Gürdal; Atan, Sabri Tankut; Kula, Ufuk
    Association mining is the conventional data mining technique for analyzing market basket data and it reveals the positive and negative associations between items. While being an integral part of transaction data, pricing and time information have not been integrated into market basket analysis in earlier studies. This paper proposes a new approach to mine price, time and domain related attributes through re-mining of association mining results. The underlying factors behind positive and negative relationships can be characterized and described through this second data mining stage. The applicability of the methodology is demonstrated through the analysis of data coming from a large apparel retail chain, and its algorithmic complexity is analyzed in comparison to the existing techniques.