Optimization of job shop scheduling problems using modified clonal selection algorithm

Authors : Yılmaz ATAY, Halife KODAZ

Pages : 1528-1539

Doi:10.3906/elk-1212-26

View : 20 | Download : 10

Publication Date : 0000-00-00

Article Type : Research Paper

Abstract :Artificial immune systems insert ignore into journalissuearticles values(AISs); are one of the artificial intelligence techniques studied a lot in recent years. AISs are based on the principles and mechanisms of the natural immune system. In this study, the clonal selection algorithm, which is used commonly in AISs, is modified. This algorithm is applied to job shop scheduling problems, which are one of the most difficult optimization problems. For applying application results to the optimum solution, parameter values giving the optimum solution are determined by analyzing the parameters in the algorithm. The obtained results are given in detail in the tables and figures. The best makespan values are reached in 7 out of 10 test problems insert ignore into journalissuearticles values(FT06, LA01, LA02, LA03, LA04, LA05, and ABZ6);. Reasonable makespan values are reached for the remaining 3 problems insert ignore into journalissuearticles values(FT10, LA16, and ABZ5);. The obtained results demonstrate that the developed system can be applied successfully to job shop scheduling problems.
Keywords : Artificial immune system, clonal selection algorithm, job shop scheduling, optimization