Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Quantum computation and quantum information
Quantum computation and quantum information
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Quantum-inspired evolutionary algorithm for a class of combinatorial optimization
IEEE Transactions on Evolutionary Computation
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As for Helical Crossover (HX), the effectiveness to Traveling Salesman Problem (TSP) has been shown in previous studies. In this paper, we apply the HX to Job-shop Scheduling Problem (JSP) in order to clarify the effectiveness of the HX to JSP besides TSP, and then we describe the result of computational experiment. Our experiment uses the ft10 (ten-jobs and ten-machines) which is a benchmark problem in JSP of H. Fisher & G. L. Thompson. The experiment clarifies that Immune Algorithm (IA) incorporating the HX works effectively to the ft10 and shows 2.4 times discovery rate of optimal solution compared with conventional IA no-incorporating the HX (classical IA).