Improved Genetic Programming Algorithm for RCMPSP

被引：0
作者：
Chen H. [1 ]
Ding G. [1 ]
Zhang J. [1 ]
Yan K. [1 ]
机构：
[1] Institute of Advanced Design and Manufacturing, School of Mechanical Engineering, Southwest Jiaotong University, Chengdu
来源：
Zhongguo Jixie Gongcheng/China Mechanical Engineering | 2021年 / 32卷 / 10期
关键词：
Genetic programming; Hyper-heuristic; Multi-objective optimization; Non-dominated sorting genetic algorithm Ⅱ; Resource constrained multi-project scheduling problem(RCMPSP);
D O I：
10.3969/j.issn.1004-132X.2021.10.010
中图分类号：
学科分类号：
摘要：
Aiming at the lack of optimization ability for priority rule scheduling, an improved hyper-heuristic genetic programming algorithm for the RCMPSP was proposed to evolve better priority rules. By analyzing the existing priority rules, a normalized attribute set and a top-level discriminant coding method for multi-project scheduling were constructed, and the NSGA-Ⅱ virtual fitness allocation method was applied to evaluate the population for achieving multi-objective optimization. A diversity population updating method was designed to enhance the search ability and avoid the defects that the traditional genetic programming was easy to fall into local optimum. The validity and feasibility of the proposed method were verified by the calculation experiments based on benchmark data set PSPLIB and the aircraft assembly line production instance. © 2021, China Mechanical Engineering Magazine Office. All right reserved.
引用
收藏
页码：1213 / 1221
页数：8
相关论文
共 32 条
  • [1] FANG Chen, WANG Ling, Survey of Study on Resource Constrained Project Scheduling, Control and Decision, 25, 5, pp. 641-650, (2010)
  • [2] HARTMANN S, BRISKORN D., A Survey of Variants and Extensions of the Resource-constrained Project Scheduling Problem, European Journal of Operational Research, 207, 1, pp. 1-14, (2010)
  • [3] BLAZEWICZ J, LENSTRA J K, KAN A H G., Scheduling Subject to Resource Constraints: Classification and Complexity, Discrete Applied Mathematics, 5, 1, pp. 11-24, (1983)
  • [4] ZHENG H, WANG L, ZHENG X., Teaching-learning-based Optimization Algorithm for Multi-skill Resource Constrained Project Scheduling Problem, Soft Computing, 21, 6, pp. 1537-1548, (2017)
  • [5] CHENG J, FOWLER J, KEMP K, Et al., Multi-mode Resource-constrained Project Scheduling Problems with Non-preemptive Activity Splitting, Computers & Operations Research, 53, pp. 275-287, (2015)
  • [6] ZHANG Shaqing, CHEN Xindu, CHEN Qingxin, Et al., Reactive Scheduling for Multiple Mould and Die Projects Based on Improved Multi-objective Particle Swarm Optimization, China Mechanical Engineering, 22, 10, pp. 1173-1179, (2010)
  • [7] WAUTERS T, KINABLE J, SMET P, Et al., The Multi-mode Resource-constrained Multi-project Scheduling Problem, Journal of Scheduling, 19, 3, pp. 271-283, (2016)
  • [8] HOMBERGER J, FINK A., Generic Negotiation Mechanisms with Side Payments: Design, Analysis and Application for Decentralized Resource-constrained Multi-project Scheduling Problems, European Journal of Operational Research, 261, 3, pp. 1001-1012, (2017)
  • [9] PAYNE J H., Management of Multiple Simultaneous Projects: a State-of-the-art Review, International Journal of Project Management, 13, 3, pp. 163-168, (1995)
  • [10] XIN S H U, SU Q, WANG Q, Et al., Optimization of Resource-constrained Multi-project Scheduling Problem Based on the Genetic Algorithm, 15th International Conference on Service Systems and Service Management (ICSSSM), pp. 1-6, (2018)
1234