Optimizing for a Resource-constrained Multi-project Scheduling Problem with Planned Resource Unavailability
- 10.2991/msam-18.2018.51How to use a DOI?
- multi-project scheduling; resource-constrained; planned resouce unavailability; genetic algorithm; particle swarm optimization; tabu search
Based on a real producing scenario, we established a resource-constrained multi-project scheduling problem with planned resource unavailability model (RCMPSP-PRU) to minimize the makespan. Different from the traditional resource-constrained multi-project scheduling model, RCMPSP-PRU introduces some new concepts such as site, movable resource and unmovable resource, and accompanied with planned resource unavailability. In order to solve RCMPSP-PRU, we firstly proposed a heuristic algorithm called ISHPR based on serial generation scheme and priority rules, then two improved algorithms named ISG-PS and ISG-PSTS was designed respectively, in which the genetic algorithm, particle swarm optimization and tabu search are incorporated. The GA and PSO algorithms were used to enhance the selection of better site for each job, and the TS was used to exploit better solutions when a resource unavailability occurred. The experimental results based on a real world instance show that ISG-PSTS has the best performance, which illustrates the effectiveness of this work. In addition, the method combined with various intelligent algorithms to solve scheduling problems can inspire later research.
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Jinwen Tian AU - Xingye Dong AU - Sheng Han PY - 2018/07 DA - 2018/07 TI - Optimizing for a Resource-constrained Multi-project Scheduling Problem with Planned Resource Unavailability BT - Proceedings of the 2018 3rd International Conference on Modelling, Simulation and Applied Mathematics (MSAM 2018) PB - Atlantis Press SP - 243 EP - 248 SN - 1951-6851 UR - https://doi.org/10.2991/msam-18.2018.51 DO - 10.2991/msam-18.2018.51 ID - Tian2018/07 ER -