In this study, we discuss the problem of permutation flowshop scheduling problem (PFSP) to reduce total energy consumption (TEC). We offer a new hybrid meta-heuristic algorithm for solving the problem. The paper aims to combine the cross entropy and genetic algorithm (CEGA) with the simulated annealing (SA) algorithm. The CEGA is applied to find the best initial solution inside the SA algorithm and the proposed algorithm is compared to previous tests of the famous NSGA-II and GA-SA algorithm. During study of the numerical test, the proposed algorithm genuinely useful is compared certain efficient algorithms of the from previous research.
Hybrid flowshop scheduling is one topic that is often reviewed by researchers at this time. Hybrid flowshop scheduling is the development of problems from pure flowshop. Flowshop problems have one machine at each stage. In this problem, each stage of operation has a machine that is arranged in parallel. This article aims to discuss the issue of hybrid flowshop scheduling at three stages to minimize makespan. Some previous studies discussed scheduling problems by considering setup time. However, such research is generally for the problem of pure flowshop. Therefore, a new algorithm is proposed to solve the problem. The proposed algorithm is developed from the Pour heuristic algorithm. Several experiments were conducted to determine the performance of the proposed algorithm. This study uses ten numerical experiments. This experiment uses the number of jobs varying from 5 jobs to 50 jobs. The results of numerical experiments show that the proposed algorithm has better performance compared to some other algorithms. The proposed method produces an effective solution if it is used to solve problems with a large number of jobs..
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