Journal
APPLIED MATHEMATICAL MODELLING
Volume 58, Issue -, Pages 181-202Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.apm.2017.09.015
Keywords
Project scheduling; Stochastic activity duration; Hierarchical alternative method; Stochastic chance constraint; Sample average approximation (SAA); Discrete artificial algae algorithm (DAAA)
Funding
- National Natural Science Foundation of China [71390521, 61473326, 71571098, 71671088, 91646123, 71701090]
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In this paper, a resource constrained project scheduling problem with hierarchical alternatives and stochastic activity durations is studied. A stochastic chance constraint is introduced to formulate this problem. A metaheuristic framework called SAA/DAAA through integrating the sampling average approximation (SAA) with the population-based evolutionary artificial algae algorithm (AAA) is developed to solve the problem due to the NP-hardness nature of the problem. The priority-selection list (PSL) and schedule generation scheme (SGS) are introduced for local search. Experiments with different sizes (50-scale, 100-scale, 150-scale) as well as different uncertainty levels (moderate, medium, high) are used as examples to illustrate and validate the proposed method. The influences of sample size, sampling times and confidence level are also analyzed during experiments. In addition, the proposed discrete AAA (DAAA) is compared with classic GA and numerical experiments show that the SAA/DAAA outperforms the SAA/GA in terms of both objectives and solving time. (C) 2017 Published by Elsevier Inc.
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