A Hybrid Discrete Bacterial Memetic Algorithm with Simulated Annealing for Optimization of the Flow Shop Scheduling Problem

This paper deals with the flow shop scheduling problem. To find optimal solution is an NP-hard The reviews some algorithms from literature and applies a benchmark dataset to evaluate their efficiency. In this research work, discrete bacterial memetic evolutionary algorithm (DBMEA) as global searcher was investigated. proposed improves local search by applying simulated annealing (SA). presents experimental results of solving no-idle compare other researchers’ problem set used. calculated makespan times were compared against best-known solutions in literature. hybrid has provided better than methods using genetic variants, thus it major improvement for family production problems.