An Improved Evolution Strategy Hybridization With Simulated Annealing for Permutation Flow Shop Scheduling Problems

Flow Shop Scheduling Problem (FSSP) has significant application in the industry, and therefore it been extensively addressed literature using different optimization techniques. Current research investigates Permutation (PFSSP) to minimize makespan Hybrid Evolution Strategy (HES SA ). Initially, a global search of solution space is performed an Improved (I.E.S.), then improved by utilizing local abilities Simulated Annealing (S.A.). I.E.S. thoroughly exploits reproduction operator, which four offsprings are generated from one parent. A double swap mutation used guide more promising areas less computational time. The rate also varied for fine-tuning results. best acts as seed S.A., further results exploring better neighborhood solutions. In insertion used, cooling parameter acceptance-rejection criteria induce randomness algorithm. proposed HES algorithm tested on well-known NP-hard benchmark problems Taillard (120 instances), performance compared with famous techniques available literature. Experimental indicate that finds fifty-four upper bounds instances, while thirty-eight instances.