Differential Lévy-Flights Bat Algorithm for Minimization Makespan in Permutation Flow Shops
The permutation flow shop problem (PFSP) is an NP-hard problem with wide engineering and theoretical background. In this paper, a differential Lévy-flights bat algorithm (DLBA) is proposed to improve basic bat algorithm for PFSP. In DLBA, LOV rule is introduced to convert the continuous position in DLBA to the discrete job permutation, the combination of NEH heuristic and random initialization is used to initialize the population with certain quality and diversity, and a virtual population neighborhoods search is used to enhance the global optimal solution and help the algorithm to escape from local optimal. Experimental results and comparisons show the effectiveness of the proposed DLBA for PFSP.
KeywordsBat Algorithm Lévy-Flight Minimization Makespan Permutation Flow Shop Scheduling Virtual Population Neighborhoods Search
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