Minimising the Makespan of Job Shop Scheduling Problem by Using Genetic Algorithm (Ga)

Abstract

The job-shop scheduling problem is a well-known problem in the field of production as well as combinational optimization. There is ‘k’ represent the operations number and ‘n’ represent no of jobs to be processed on ‘m’ no of machines with a definite objective function to be optimized makespan (total time to compilation of operations on a particular task)in job-shop scheduling problem. The particular work adopted a modified genetic algorithm approach is proposed with operating parameters i.e., size of population 50, operation chromosome based structure, selection scheme used as tournament selection, crossover two-point random with a probability 80% (Probc= 0.8),mutation two-point with a probability 20% (Probm= 0.2), elitism is also active, repairing of chromosomes and no. of iteration (termination) is 1000. Genetic algorithm is programmed for job shop environment create with the help of MATLAB 2009 a 7.8. The proposed Genetic Algorithm (GA) with certain operating parameters is applied to the two problems which are taken from literature. The results obtained from modified Genetic Algorithm show that the best optimization technique for solving the job shop scheduling problems in manufacturing systems is genetic algorithm with modified operating parameter selected in these research implications to more practical and integrated problems.