Multi-constraint system scheduling using dynamic and delay ant colony system

Authors:
Shih-Tang Lo;Ruey-Maw Chen;Yueh-Min Huang
Affiliations:
Department of Information Management, Kun-Shan University, Yung-Kang City, Tainan Hsien, Taiwan, ROC;Department of Computer Science and Information Engineering, National Chin-yi University of Technology, Taichung, Taiwan, ROC;Department of Engineering Science, National Cheng-Kung University, Tainan, Taiwan, ROC
Venue:
IEA/AIE'07 Proceedings of the 20th international conference on Industrial, engineering, and other applications of applied intelligent systems
Year:
2007

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Abstract

This study presents and evaluates a modified ant colony optimization (ACO) approach for the precedence and resource-constrained multiprocessor scheduling problems. A modified ant colony system, with two designed rules, called dynamic and delay ant colony system, is proposed to solve the scheduling problems. The dynamic rule is designed to modify the latest starting time of jobs and hence the heuristic function. A delay solution generation rule in exploration of the search solution space is used to escape the local optimal solution. Simulation results demonstrate that the proposed modified ant colony system algorithm provides an effective and efficient approach for solving multiprocessor system scheduling problems with precedence and resource constraints.