Q
Quan-Ke Pan
Researcher at Shanghai University
Publications - 304
Citations - 15638
Quan-Ke Pan is an academic researcher from Shanghai University. The author has contributed to research in topics: Job shop scheduling & Local search (optimization). The author has an hindex of 62, co-authored 281 publications receiving 12128 citations. Previous affiliations of Quan-Ke Pan include Liaocheng University & Huazhong University of Science and Technology.
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A multiobjective evolutionary algorithm based on decomposition for hybrid flowshop green scheduling problem
TL;DR: A multi-objective optimization model with the objectives of minimizing the makespan and total energy consumption is developed and a multiobjective discrete artificial bee colony algorithm (MDABC) based on decomposition is suggested to solve this complex problem.
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A chaotic harmony search algorithm for the flow shop scheduling problem with limited buffers
Quan-Ke Pan,Ling Wang,Liang Gao +2 more
TL;DR: It is shown that the proposed chaotic harmony search (CHS) algorithm generates better results not only than the two recently developed harmony search algorithms but also than the existing hybrid genetic algorithm and hybrid particle swarm optimization in terms of solution quality and robustness.
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An effective discrete harmony search algorithm for flexible job shop scheduling problem with fuzzy processing time
TL;DR: In this paper, a discrete harmony search (DHS) algorithm is proposed for FJSP with fuzzy processing time, where the objective is to minimize maximum fuzzy completion time and a simple and effective heuristic rule is proposed to initialise harmony population.
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A shuffled multi-swarm micro-migrating birds optimizer for a multi-resource-constrained flexible job shop scheduling problem
Liang Gao,Quan-Ke Pan +1 more
TL;DR: The results demonstrate that the proposed SM2-MBO performs significantly better than the existing algorithms in solving the multi-resource-constrained flexible job shop scheduling problem with the makespan criterion.
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A discrete artificial bee colony algorithm for distributed hybrid flowshop scheduling problem with sequence-dependent setup times
TL;DR: A machine position-based mathematical model and a discrete artificial bee colony algorithm (DABC) for the DHFSP-SDST to optimise the makespan and results and statistical analyses validate that the DABC outperforms the best performing algorithm in the literature.