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.
Papers
More filters
Journal ArticleDOI
A variable iterated greedy algorithm with differential evolution for the no-idle permutation flowshop scheduling problem
TL;DR: A variable iterated greedy algorithm (IG) with differential evolution (vIG_DE) designed to solve the no-idle permutation flowshop scheduling problem and computational results show that all three IG variants represent state-of-art methods for the NIPFS problem.
Journal ArticleDOI
A hybrid particle swarm optimization with estimation of distribution algorithm for solving permutation flowshop scheduling problem
TL;DR: The computational experiment on different benchmark suites in PFSP shows a superiority of PSO-EDA over other counterpart algorithms in terms of accuracy.
Journal ArticleDOI
A discrete artificial bee colony algorithm for the no-idle permutation flowshop scheduling problem with the total tardiness criterion
TL;DR: In this paper, a discrete artificial bee colony algorithm was proposed to solve the no-idle permutation flowshop scheduling problem with the total tardiness criterion, where idle time is not allowed on machines.
Journal ArticleDOI
Discrete harmony search algorithm for the no-wait flow shop scheduling problem with total flow time criterion
TL;DR: In this article, a discrete harmony search algorithm (DHS) is developed for solving the no-wait flow shop scheduling problem with the objective to minimize total flowtime, where a harmony is represented as a discrete job permutation and a new heuristic based on the well-known NEH method is proposed to initialize the harmony memory.
Journal ArticleDOI
An improved fruit fly optimization algorithm for solving the multidimensional knapsack problem
Tao Meng,Quan-Ke Pan +1 more
TL;DR: An improved fruit fly optimization algorithm (IFFOA) for solving the multidimensional knapsack problem (MKP) and a modified harmony search algorithm (MHS) is proposed and applied to add cooperation among swarms in IFFOA to make full use of swarm intelligence.