Invasive weed optimization algorithm for optimization no-idle flow shop scheduling problem

Abstract In this paper, an invasive weed optimization (IWO) scheduling algorithm is presented for optimization no-idle flow-shop scheduling problem (NFSP) with the criterion to minimize the maximum completion time (makespan). Firstly, a simple approach is put forward to calculate the makespan of job sequence. Secondly, the most position value (MPV) method is used to code the weed individuals so that fitness values can be calculated. Then, use the global exploration capacity of IWO to select the best fitness value and its corresponding processing sequence of job by evaluating the fitness of individuals. The results of 12 different scale NFSP benchmarks compared with other algorithms show that NFSP can be effectively solved by IWO with stronger robustness.

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