首页|Applying Genetic Algorithm to Resource Constrained Multi-Project Scheduling Problems

Applying Genetic Algorithm to Resource Constrained Multi-Project Scheduling Problems

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Resource-constrained multi-project scheduling problems (RCMPSP) consider precedence relationship among activities and the capacity constraints of multiple resources for multiple projects. RCMPSP are NP-hard due to these practical constraints indicating an exponential calculation time to reach optimal solution. In order to improve the speed and the performance of problem solving, heuristic approaches are widely applied to solve RCMPSP. This research proposes Hybrid Genetic Algorithm (HGA) and heuristic approach to solve RCMPSP with an objective to minimize the total tardiness. HGA is compared with three typical heuristics for RCMPSP: Maximum Total Work Content, Earliest Due Date, and Minimum Slack. Two typical RCMPSP from literature are used as a test bed for performance evaluation. The results demonstrate that HGA outperforms the three heuristic methods in term of the total tardiness.

resource-constrained multi-project scheduling problemsgenetic algorithmheuristic method

James C. Chen、Wun-Hao Jaong、Cheng-Ju Sun、Hung-Yu Lee、Jenn-Sheng Wu、Chung-Chao Ku

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Department of Industrial and Systems Engineering, Chung Yuan Christian University, Chung Li, Taiwan 32023, R.O.C

Mechanical and Systems Research Laboratories, Industrial Technology Research Institute, Sec. 4, Zhongxing Rd., Chutung, Hsinchu, Taiwan 31040, R.O.C.

2010

Key engineering materials

Key engineering materials

ISSN：1013-9826
年,卷(期)：2010.419/420