Intelligent Engineering Systems through Artificial Neural Networks, Volume 16
8 A Genetic Fuzzy Approach for Multi-Objective Single Machine Scheduling
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This paper seeks to determine the feasibility of using fuzzy concepts in conjunction with genetic algorithms in order to solve multi-objective decision making problems. The domain chosen is the area of single machine scheduling. Another focus of this research is to test the feasibility of gene detection strategies to perform block crossover during the evolution cycle of the genetic algorithm. During block crossover, the good gene segments from the parent chromosomes are preserved in the child chromosomes. Several problems with known optimal solutions for non-zero ready times are tested using the proposed method and results are reported. The results indicate that the proposed method found the optimal solution in 20-job category with high frequency.