Stochastic Project Scheduling with Hierarchical Alternatives
© 2017 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 aver...
| Main Authors: | , , , |
|---|---|
| Format: | Journal Article |
| Published: |
Elsevier
2018
|
| Online Access: | http://hdl.handle.net/20.500.11937/67034 |
| _version_ | 1848761457572839424 |
|---|---|
| author | Tao, S. Wu, Changzhi Sheng, Z. Wang, Xiangyu |
| author_facet | Tao, S. Wu, Changzhi Sheng, Z. Wang, Xiangyu |
| author_sort | Tao, S. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | © 2017 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. |
| first_indexed | 2025-11-14T10:31:59Z |
| format | Journal Article |
| id | curtin-20.500.11937-67034 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T10:31:59Z |
| publishDate | 2018 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-670342018-05-18T08:04:54Z Stochastic Project Scheduling with Hierarchical Alternatives Tao, S. Wu, Changzhi Sheng, Z. Wang, Xiangyu © 2017 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. 2018 Journal Article http://hdl.handle.net/20.500.11937/67034 10.1016/j.apm.2017.09.015 Elsevier restricted |
| spellingShingle | Tao, S. Wu, Changzhi Sheng, Z. Wang, Xiangyu Stochastic Project Scheduling with Hierarchical Alternatives |
| title | Stochastic Project Scheduling with Hierarchical Alternatives |
| title_full | Stochastic Project Scheduling with Hierarchical Alternatives |
| title_fullStr | Stochastic Project Scheduling with Hierarchical Alternatives |
| title_full_unstemmed | Stochastic Project Scheduling with Hierarchical Alternatives |
| title_short | Stochastic Project Scheduling with Hierarchical Alternatives |
| title_sort | stochastic project scheduling with hierarchical alternatives |
| url | http://hdl.handle.net/20.500.11937/67034 |