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A Cost Optimization Model for Multiresource Leveling Problem without Project Duration Constraint

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  • Qingyou Yan
  • Qian Zhang
  • Xin Zou

Abstract

The study of traditional resource leveling problem aims at minimizing the resource usage fluctuations and obtaining sustainable resource supplement, which is accomplished by adjusting noncritical activities within their start and finish time. However, there exist limitations in terms of the traditional resource leveling problem based on the fixed project duration. This paper assumes that the duration can be changed in a certain range and then analyzes the relationship between the scarce resource usage fluctuations and project cost. This paper proposes an optimization model for the multiresource leveling problem. We take into consideration five kinds of cost: the extra hire cost when the resource demand is greater than the resource available amount, the idle cost of resource when the resource available amount is greater than the resource demand, the indirect cost related to the duration, the liquidated damages when the project duration is extended, and the incentive fee when the project duration is reduced. The optimal objective of this model is to minimize the sum of the aforementioned five kinds of cost. Finally, a case study is examined to highlight the characteristic of the proposed model at the end of this paper.

Suggested Citation

  • Qingyou Yan & Qian Zhang & Xin Zou, 2016. "A Cost Optimization Model for Multiresource Leveling Problem without Project Duration Constraint," Discrete Dynamics in Nature and Society, Hindawi, vol. 2016, pages 1-8, July.
    • Handle: RePEc:hin:jnddns:1514959
    DOI: 10.1155/2016/1514959
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    References listed on IDEAS

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    1. Erik Demeulemeester, 1995. "Minimizing Resource Availability Costs in Time-Limited Project Networks," Management Science, INFORMS, vol. 41(10), pages 1590-1598, October.
    2. Rodrigues, Sávio B. & Yamashita, Denise S., 2010. "An exact algorithm for minimizing resource availability costs in project scheduling," European Journal of Operational Research, Elsevier, vol. 206(3), pages 562-568, November.
    3. A Drexl & A Kimms, 2001. "Optimization guided lower and upper bounds for the resource investment problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(3), pages 340-351, March.
    4. Bandelloni, M. & Tucci, M. & Rinaldi, R., 1994. "Optimal resource leveling using non-serial dyanamic programming," European Journal of Operational Research, Elsevier, vol. 78(2), pages 162-177, October.
    5. Neumann, K. & Zimmermann, J., 2000. "Procedures for resource leveling and net present value problems in project scheduling with general temporal and resource constraints," European Journal of Operational Research, Elsevier, vol. 127(2), pages 425-443, December.
    6. Rieck, Julia & Zimmermann, Jürgen & Gather, Thorsten, 2012. "Mixed-integer linear programming for resource leveling problems," European Journal of Operational Research, Elsevier, vol. 221(1), pages 27-37.
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