A Novel Genetic Simulated Annealing Algorithm for No-wait Hybrid Flowshop Problem with Unrelated Parallel Machines

This paper studies the problem of scheduling N jobs in a hybrid flowshop with unrelated parallel machines at each stage. Considering practical application presented problem, no-wait constraints and objective function total flowtime are included problem. A mathematical model is constructed novel genetic simulated annealing algorithm so-called GSAA developed to solve this In algorithm, firstly modified NEH proposed obtain initial population. two-dimensional matrix encoding scheme for solutions designed an insertion-translation approach employed decoding order meet constraints. Afterwards, avoid GA premature enhance search ability, adaptive adjustment strategy imposed on crossover mutation operators. addition, SA procedure implemented some better individuals from complete re-optimization, where five neighborhood structures including job based exchange, gene insertion, mutation, mutation. Finally, various simulation experiments two scales small-medium large established. Computational results show that performs much more effectively compared several heuristic algorithms reported literature.