Helical crossover method in immune algorithm: a case for job-shop scheduling problem
Ichiro Iimura, Ryo HIRAMI, Yoshifumi Moriyama, Shigeru Nakayama · International Conference on Intelligent Systems and Control · 2007
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).