探索流程车间调度的启发式技术

IF 0.9 Q4 ENGINEERING, INDUSTRIAL
Zuzana Soltysova, Pavol Semanco, Jan Modrak
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Exploring heuristic techniques for flow shop scheduling
This paper explores selected heuristics methods, namely CDS, Palmer’s slope index, Gupta’s algorithm, and concurrent heuristic algorithm for minimizing the makespan in permutation flow shop scheduling problem. Its main scope is to explore how different instances sizes impact on performance variability. The computational experiment includes 12 of available benchmark data sets of 10 problems proposed by Taillard. The results are computed and presented in the form of relative percentage deviation, while outputs of the NEH algorithm were used as reference solutions for comparison purposes. Finally, pertinent findings are commented.
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来源期刊
CiteScore
2.80
自引率
21.40%
发文量
0
期刊介绍: Management and Production Engineering Review (MPER) is a peer-refereed, international, multidisciplinary journal covering a broad spectrum of topics in production engineering and management. Production engineering is a currently developing stream of science encompassing planning, design, implementation and management of production and logistic systems. Orientation towards human resources factor differentiates production engineering from other technical disciplines. The journal aims to advance the theoretical and applied knowledge of this rapidly evolving field, with a special focus on production management, organisation of production processes, management of production knowledge, computer integrated management of production flow, enterprise effectiveness, maintainability and sustainable manufacturing, productivity and organisation, forecasting, modelling and simulation, decision making systems, project management, innovation management and technology transfer, quality engineering and safety at work, supply chain optimization and logistics. Management and Production Engineering Review is published under the auspices of the Polish Academy of Sciences Committee on Production Engineering and Polish Association for Production Management.
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