Resource-constrained project scheduling with cash flows occurs in many settings, ranging from research and development to commercial and residential construction. Although efforts have been made to develop efficient optimal procedures to maximize the net present value of cash flows for resource-cons
A metaheuristic scheduling procedure for resource-constrained projects with cash flows
β Scribed by Dan Zhu; Rema Padman
- Publisher
- John Wiley and Sons
- Year
- 1999
- Tongue
- English
- Weight
- 244 KB
- Volume
- 46
- Category
- Article
- ISSN
- 0894-069X
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β¦ Synopsis
Resource-constrained project scheduling problems with cash flows (RCPSPCF) are complex, combinatorial optimization problems. Many heuristics have been reported in the literature that produce reasonable schedules in limited project environments. However, the lack of a heuristic that dominates under differing project conditions can lead to a suboptimal choice of an appropriate heuristic for scheduling any given project. This may result in poor schedules and monetary losses. This paper reports on the application of the tabu search metaheuristic procedure for the RCPSPCF. Strategies for neighborhood generation and candidate selection that exploit the special features of the problem are combined with a simple multiheuristic start procedure. Extensive experimentation, with multiple data sets and comparison with an upper bound, indicates a significant improvement, both in project Net Present Value (NPV) as well as the number of projects, where the metaheuristic outperforms the best known heuristics in the literature. More specifically, this procedure produces the best schedules in over 85% of the projects tested, in contrast to the best single-pass heuristics which have been shown to dominate in at most 20% of the same cases. This iterative, general purpose heuristic is able to adapt significantly better to the complex interactions of the many critical parameters of the RCPSPCF than single-pass heuristics that use more specific information about each project environment.
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