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A Two Stage Search Heuristic for Scheduling Payments in Projects

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  • Nalini Dayanand
  • Rema Padman

Abstract

When the Net Present Value (NPV) of a project is used as a measure of its financial performance, effective management of cash flows over the duration of the project is critical for improved profitability. Progress payments are a major component of project cash flows. In many project environments, the contractor can negotiate payment terms. Payments are typically tied to completion of project activities and therefore have significant impact on the schedule of activities and the timing of the payments. In this paper, we consider the problem of simultaneously determining the amount, timing and location of progress payments in projects to maximize NPV. Due to the combinatorial nature of the problem, heuristics are a practical approach to solving the problem. We propose a two-stage heuristic where simulated annealing is used in the first stage to determine a set of payments. In the second stage, activities are rescheduled to improve project NPV. We compare the performance of this general purpose heuristic with other problem-dependent heuristics from the literature. Our results indicate that the simulated annealing heuristic significantly outperforms the parameter-based heuristics. Although rescheduling in the second stage improves NPV, increases are relatively small in magnitude. While the specific parameters settings suggested by the simulated annealing heuristic in this study may have limited generalizability at this time due to the narrow range of problems tested, our analysis suggests that a pure simulated annealing approach is a very attractive alternative for obtaining good heuristic solutions to the complex problem of scheduling payments in projects. Copyright Kluwer Academic Publishers 2001

Suggested Citation

  • Nalini Dayanand & Rema Padman, 2001. "A Two Stage Search Heuristic for Scheduling Payments in Projects," Annals of Operations Research, Springer, vol. 102(1), pages 197-220, February.
  • Handle: RePEc:spr:annopr:v:102:y:2001:i:1:p:197-220:10.1023/a:1010910316909
    DOI: 10.1023/A:1010910316909
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    Citations

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    Cited by:

    1. Luis F. Machado-Domínguez & Carlos D. Paternina-Arboleda & Jorge I. Vélez & Agustín Barrios-Sarmiento, 2022. "An adaptative bacterial foraging optimization algorithm for solving the MRCPSP with discounted cash flows," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 30(2), pages 221-248, July.
    2. Leyman, Pieter & Vanhoucke, Mario, 2017. "Capital- and resource-constrained project scheduling with net present value optimization," European Journal of Operational Research, Elsevier, vol. 256(3), pages 757-776.
    3. He, Zhengwen & Liu, Renjing & Jia, Tao, 2012. "Metaheuristics for multi-mode capital-constrained project payment scheduling," European Journal of Operational Research, Elsevier, vol. 223(3), pages 605-613.
    4. He, Zhengwen & Xu, Yu, 2008. "Multi-mode project payment scheduling problems with bonus-penalty structure," European Journal of Operational Research, Elsevier, vol. 189(3), pages 1191-1207, September.
    5. Zhengwen He & Nengmin Wang & Pengxiang Li, 2014. "Simulated annealing for financing cost distribution based project payment scheduling from a joint perspective," Annals of Operations Research, Springer, vol. 213(1), pages 203-220, February.
    6. He, Zhengwen & Wang, Nengmin & Jia, Tao & Xu, Yu, 2009. "Simulated annealing and tabu search for multi-mode project payment scheduling," European Journal of Operational Research, Elsevier, vol. 198(3), pages 688-696, November.
    7. Mika, Marek & Waligora, Grzegorz & Weglarz, Jan, 2005. "Simulated annealing and tabu search for multi-mode resource-constrained project scheduling with positive discounted cash flows and different payment models," European Journal of Operational Research, Elsevier, vol. 164(3), pages 639-668, August.

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