Minimization of Total Weighted Tardiness and Makespan for SDST Flow Shop Scheduling using Genetic Algorithm

In the present work, SDST flow shop scheduling with minimizing the weighted sum of total weighted tardiness and makespan have been considered simultaneously. Four modified heuristic have been proposed for preliminary viable sequence. Sequence obtained from the modified heuristics is combined with the initial seed sequence of genetic algorithm and called as Genetic Algorithm (GA). Hence four different GAs named as GA 1 , GA 2 , GA 3 and GA 4 with further classical GA called as GA 5 have been presented for bi-criteria SDST flow shop scheduling problem for comparative analysis amongst them. Bi-criteria fitness function proposed for scheduling the jobs in SDST flow shop proves to be efficient and flexible for minimizing the due date and completion time related performance measures. From the comparative analysis among different GAs considered, it has been found that the performance of algorithm varies with the size of job and machines. It has also been concluded that GA 3 shows better results over other for all the problems considered upto 200 jobs and 20 machines including sequence dependent set up time.