An adaptive dynamic neighborhood crow search algorithm for solving permutation flow shop scheduling problems
نویسندگان
چکیده
To effectively solve the permutation flow-shop scheduling problem (PFSP), an adaptive dynamic neighborhood crow search algorithm (AdnCSA) is proposed to minimize makespan. Firstly, a modified heuristic based on nawaz-enscore-ham (NEH) was improve quality and diversity of initial population. Secondly, smallest-position-value (SPV) rule used encode population so that it can handle discrete problem. Lastly, top 20% individuals with best fitness selected execute search, structure introduced balance global local ability algorithm. evaluate effectiveness method, Rec Taillard benchmarks were test performance. Compared nine recent metaheuristic method for solving PFSP, numerical results produced by AdnCSA are promising show great potential
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ژورنال
عنوان ژورنال: Journal of Industrial and Management Optimization
سال: 2023
ISSN: ['1547-5816', '1553-166X']
DOI: https://doi.org/10.3934/jimo.2023070