Helical Crossover Method in Immune Algorithm: A Case for Job-Shop Scheduling Problem

I. Iimura, R. Hirami, Y. Moriyama, and S. Nakayama (Japan)


Immune Algorithm, Helical Crossover, Interference Crossover, Job-Shop Scheduling Problem.


As for Helical Crossover (HX), the effectiveness to Trav eling Salesman Problem (TSP) has been shown in previ ous studies. In this paper, we apply the HX to Job-shop Scheduling Problem (JSP) in order to clarify the effective ness 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 exper iment 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 conven tional IA no-incorporating the HX (classical IA).

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