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Four Payment Models for the Multi-Mode Resource Constrained Project Scheduling Problem with Discounted Cash Flows

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Abstract

In this paper, the multi-mode resource constrained project scheduling problem with discounted cash flows is considered. The objective is the maximization of the net present value of all cash flows. Time value of money is taken into consideration, and cash in- and out-flows are associated with activities and/or events. The resources can be of renewable, nonrenewable, and doubly constrained resource types. Four payment models are considered: lump sum payment at the terminal event, payments at prespecified event nodes, payments at prespecified time points and progress payments. For finding solutions to problems proposed, a genetic algorithm (GA) approach is employed, which uses a special crossover operator that can exploit the multi-component nature of the problem. The models are investigated at the hand of an example problem. Sensitivity analyses are performed over the mark up and the discount rate. A set of 93 problems from literature are solved under the four different payment models and resource type combinations with the GA approach employed resulting in satisfactory computation times. The GA approach is compared with a domain specific heuristic for the lump sum payment case with renewable resources and is shown to outperform it.

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Authors and Affiliations

  1. Manufacturing Systems Engineering, Faculty of Engineering and Natural Sciences, Sabancı University, Orhanlı, Tuzla, 81474, Istanbul, Turkey

    Gündüz Ulusoy

  2. Abant İzzet Baysal University Management School, Bolu, Turkey

    Funda Sivrikaya-Şerifoğlu

  3. Department of Industrial Engineering, Boğaziçi University, Bebek, Istanbul, Turkey

    Şule Şahin

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  1. Gündüz Ulusoy
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  2. Funda Sivrikaya-Şerifoğlu
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  3. Şule Şahin
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Ulusoy, G., Sivrikaya-Şerifoğlu, F. & Şahin, Ş. Four Payment Models for the Multi-Mode Resource Constrained Project Scheduling Problem with Discounted Cash Flows. Annals of Operations Research 102, 237–261 (2001). https://doi.org/10.1023/A:1010914417817

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