Integrated decision making model and algorithm of project splitting and multi-project scheduling

被引：0
|
作者：
Yang C. [1 ]
Lu Z. [1 ]
机构：
[1] School of Mechanical Engineering, Tongji University, Shanghai
来源：
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2018年 / 24卷 / 03期
基金：
中国国家自然科学基金;
关键词：
Advanced parallel scheduling; Multi-project scheduling; Project splitting; Tabu search; Time-resource utilization rule;
D O I：
10.13196/j.cims.2018.03.002
中图分类号：
学科分类号：
摘要：
Aiming at the problem that several aircrafts shared assembly line resources in actual aircraft moving assembly line, and by considering the periodical scheduling requirement of assembly line resources, the process of aircraft moving assembly was abstracted as a resource constrained multi-project scheduling problem based on project splitting through splitting assembly task package of an aircraft into several sub-packages with simultaneous scheduling. A mathematical model was formulated to make decision of project splitting and multi-project scheduling, and a two-level iterative algorithm was built to solve the model. A job allocation heuristic algorithm based on tabu search was applied in the first level to allocate jobs between projects, and the Time Resource Utilization (TRU) rule based on advanced parallel schedule generation scheme was presented in the second level to generate feasible schedules. Numeral experiment was used to show the effectiveness of proposed method. © 2018, Editorial Department of CIMS. All right reserved.
引用
收藏
页码：550 / 557
页数：7
相关论文
共 13 条
  • [1] Mastor A.A., An experimental investigation and comparative evaluation of production line balancing techniques, Management Science, 16, 11, pp. 728-746, (1970)
  • [2] Browning T.R., Yassine A.A., Resource-constrained multi-project scheduling: priority rule performance revisited, International Journal of Production Economics, 126, 2, pp. 212-228, (2010)
  • [3] Blazewicz J., Lenstra J.K., Rinnooy K.A.H.G., Scheduling subject to resource constraints: classification and complexity, Discrete Applied Mathematics, 5, 1, pp. 11-24, (1983)
  • [4] Kim K.W., Yun Y.S., Yoon J.M., Gen M., Yamazaki G., Hybrid genetic algorithm with adaptive abilities for resource-constrained multiple project scheduling, Computers in Industry, 56, 2, pp. 143-160, (2005)
  • [5] He H., He Z., Liu R., Scheduling optimization of multi-project overdue penalty minimization based on resource sharing, Industrial Engineering and Management, 20, 6, pp. 69-75, (2015)
  • [6] Gao J., Guo S., Du B., An ant colony algorithm for resource-constrained multi-project zcheduling problem, Journal of Wuhan University of Technology: Transportation Science & Engineering, 37, 1, pp. 183-186, (2013)
  • [7] Wang W., Wang X., Ge X., Multi-objective optimization model for multi-project scheduling on critical chain, Advances in Engineering Software, 68, 1, pp. 33-39, (2014)
  • [8] Wang W., Wang X., Ge X., Multi-mode and multi-project scheduling modeling and algorithm with activity splitting, Computer Integrated Manufacturing Systems, 20, 6, pp. 1388-1397, (2014)
  • [9] Asta S., Karapetyan D., Kheiri A., Combining Mon- te-Carlo and hyper-heuristic methods for the multi-mode resource-constrained multi-project scheduling problem, Information Sciences, 373, pp. 476-498, (2016)
  • [10] Kruger D., Scholl A., A heuristic solution framework for the resource constrained(multi-)project scheduling problem with sequence-dependent transfer times, European Journal of Operational Research, 197, 2, pp. 492-508, (2009)
12