Modeling of and algorithm for resource-constrained project scheduling problem with resource allocation dependent processing time

被引：0
|
作者：
Liu X. [1 ]
Lu Z. [1 ]
机构：
[1] School of Mechanical and Energy Engineering, Tongji University, Shanghai
来源：
Shanghai Jiaotong Daxue Xuebao/Journal of Shanghai Jiaotong University | 2017年 / 51卷 / 01期
关键词：
2-opt local search; Controllable; Genetic algorithm; Processing time; Project scheduling; Resource allocation;
D O I：
10.16183/j.cnki.jsjtu.2017.01.014
中图分类号：
学科分类号：
摘要：
In classical resource-constrained project scheduling problems, the job processing times are assumed to be constant parameters. However, in many practical cases, the processing times depend on the resource allocated to the job. In this paper, the resource-constrained project scheduling problem was introduced with resource allocation dependent processing time to minimize the duration of the project. A model was established and a genetic algorithm was proposed to solve the problem. To improve the ability of the algorithm, a 1-opt based local search scheme and a 2-opt based local search scheme were introduced.The related properties between different job combinations and the objective of the problem were summarized and proved. Based on these properties, the approach for selecting effective job combinations was established, which greatly improved the efficiency of the algorithm in local search. Comparative computational results reveal that the algorithm proposed in this paper can solve the problem effectively. © 2017, Shanghai Jiao Tong University Press. All right reserved.
引用
收藏
页码：82 / 89
页数：7
相关论文
共 17 条
  • [11] Jozefowska J., Mika M., Rozycki R., Et al., Simulated annealing for multi-mode resource-constrained project scheduling, Annals of Operations Research, 102, 1, pp. 137-155, (2001)
  • [12] He Z., Xu Y., Multi-mode project payment scheduling problems with bonus-penalty structure, European Journal of Operational Research, 189, 3, pp. 1191-1207, (2008)
  • [13] Lova A., Tormos P., Cervantes M., Et al., An efficient hybrid genetic algorithm for scheduling projects with resource constraints and multiple execution modes, International Journal of Production Economics, 117, 2, pp. 302-316, (2009)
  • [14] Ling W., Chen F., An effective shuffled frog-leaping algorithm for multi-mode resource-constrained project scheduling problem, Information Science, 181, 20, pp. 4804-4822, (2011)
  • [15] Hartmann S., Project scheduling with multiple modes: A genetic algorithm, Annals of Operations Research, 102, pp. 111-135, (2001)
  • [16] Peteghem V.V., Vanhanhoucke M., A genetic algorithm for the preemptive and non-preemptive multi-mode resource-constrained project scheduling problem, European Journal of Operational Research, 201, 2, pp. 409-418, (2010)
  • [17] Elloumi S., Fortemps P., A hybrid rank-based evolutionary algorithm applied to multi-mode resource-constrained project scheduling problem, European Journal of Operational Research, 205, 1, pp. 31-41, (2010)
12