JACIII Vol.11 No.9 pp. 1092-1098
doi: 10.20965/jaciii.2007.p1092


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

February 15, 2007
June 14, 2007
November 20, 2007
scheduling, genetic algorithms, crossover operators, mutation operators

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.

Cite this article as:
António Ferrolho and Manuel Crisóstomo, “Optimization of Genetic Operators for Scheduling Problems,” J. Adv. Comput. Intell. Intell. Inform., Vol.11, No.9, pp. 1092-1098, 2007.
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Last updated on Feb. 25, 2021