Paper:
Language: English:
Optimization of Genetic Operators for Scheduling Problems
António Ferrolho* and Manuel Crisóstomo**
*Dept. of Electrotechnical Engineering, Superior School of Technology, Polytechnic Institute of Viseu, 3504-510 Viseu, Portugal
**Institute of Systems and Robotics, Dept. of Electrical and Computer Science Engineering, University of Coimbra, Polo II, 3030-290 Coimbra, Portugal
Received: February 15, 2007
Accepted: June 14, 2007
Keywords: scheduling, genetic algorithms, crossover operators, mutation operators
Journal ref: Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.11, No.9 pp. 1092-1098, 2007
Abstract
Genetic algorithms (GA) can provide good solutions for scheduling problems. But, when a GA is applied to scheduling problems various crossovers and mutations operators can be applicable. This paper presents and examines a new concept of genetic operators for scheduling problems. A software tool called hybrid and flexible genetic algorithm (HybFlexGA) was developed to examine the performance of various crossover and mutation operators by computing simulations of job scheduling problems.
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Reference
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