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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

The distributed assembly permutation flowshop scheduling problem with flexible assembly and batch delivery
Shengluo Yang, Zhigang Xu
International Journal of Production Research (2020) Vol. 59, Iss. 13, pp. 4053-4071
Closed Access | Times Cited: 76

Showing 1-25 of 76 citing articles:

Iterated Greedy Algorithms for Flow-Shop Scheduling Problems: A Tutorial
Ziyan Zhao, MengChu Zhou, Shixin Liu
IEEE Transactions on Automation Science and Engineering (2021) Vol. 19, Iss. 3, pp. 1941-1959
Closed Access | Times Cited: 153
Distributed scheduling problems in intelligent manufacturing systems
Yaping Fu, Yushuang Hou, Zifan Wang, et al.
Tsinghua Science & Technology (2021) Vol. 26, Iss. 5, pp. 625-645
Open Access | Times Cited: 141
Improved meta-heuristics with Q-learning for solving distributed assembly permutation flowshop scheduling problems
Hui Yu, Kaizhou Gao, Zhenfang Ma, et al.
Swarm and Evolutionary Computation (2023) Vol. 80, pp. 101335-101335
Closed Access | Times Cited: 40
An improved iterated greedy algorithm for the distributed assembly permutation flowshop scheduling problem
Ying‐Ying Huang, Quan-Ke Pan, Jiang‐Ping Huang, et al.
Computers & Industrial Engineering (2020) Vol. 152, pp. 107021-107021
Closed Access | Times Cited: 100
Energy-efficient distributed heterogeneous welding flow shop scheduling problem using a modified MOEA/D
Guangchen Wang, Xinyu Li, Liang Gao, et al.
Swarm and Evolutionary Computation (2021) Vol. 62, pp. 100858-100858
Closed Access | Times Cited: 88
A cooperative memetic algorithm with feedback for the energy-aware distributed flow-shops with flexible assembly scheduling
Jingjing Wang, Ling Wang
Computers & Industrial Engineering (2022) Vol. 168, pp. 108126-108126
Closed Access | Times Cited: 64
Intelligent scheduling and reconfiguration via deep reinforcement learning in smart manufacturing
Shengluo Yang, Zhigang Xu
International Journal of Production Research (2021) Vol. 60, Iss. 16, pp. 4936-4953
Closed Access | Times Cited: 55
Real-time scheduling for distributed permutation flowshops with dynamic job arrivals using deep reinforcement learning
Shengluo Yang, Junyi Wang, Zhigang Xu
Advanced Engineering Informatics (2022) Vol. 54, pp. 101776-101776
Closed Access | Times Cited: 49
Distributed Co-Evolutionary Memetic Algorithm for Distributed Hybrid Differentiation Flowshop Scheduling Problem
Guanghui Zhang, Bo Liu, Ling Wang, et al.
IEEE Transactions on Evolutionary Computation (2022) Vol. 26, Iss. 5, pp. 1043-1057
Closed Access | Times Cited: 39
A multiobjective memetic algorithm with particle swarm optimization and Q-learning-based local search for energy-efficient distributed heterogeneous hybrid flow-shop scheduling problem
Wenqiang Zhang, Chen Li, Mitsuo Gen, et al.
Expert Systems with Applications (2023) Vol. 237, pp. 121570-121570
Closed Access | Times Cited: 37
Historical information based iterated greedy algorithm for distributed flowshop group scheduling problem with sequence-dependent setup times
Xuan He, Quan-Ke Pan, Liang Gao, et al.
Omega (2023) Vol. 123, pp. 102997-102997
Closed Access | Times Cited: 31
An effective hyper heuristic-based memetic algorithm for the distributed assembly permutation flow-shop scheduling problem
Hongbo Song, You-Hong Yang, Jian Lin, et al.
Applied Soft Computing (2023) Vol. 135, pp. 110022-110022
Closed Access | Times Cited: 26
Models and algorithms for production planning, scheduling and sequencing problems: A holistic framework and a systematic review
Eduardo Guzmán, Beatriz Andrés, Raúl Poler
Journal of Industrial Information Integration (2021) Vol. 27, pp. 100287-100287
Open Access | Times Cited: 54
Intelligent Decision-Making of Scheduling for Dynamic Permutation Flowshop via Deep Reinforcement Learning
Shengluo Yang, Zhigang Xu, Junyi Wang
Sensors (2021) Vol. 21, Iss. 3, pp. 1019-1019
Open Access | Times Cited: 41
An effective memetic algorithm for the distributed flowshop scheduling problem with an assemble machine
Ying‐Ying Huang, Quan-Ke Pan, Liang Gao
International Journal of Production Research (2022) Vol. 61, Iss. 6, pp. 1755-1770
Closed Access | Times Cited: 33
Self-Adaptive Population-Based Iterated Greedy Algorithm for Distributed Permutation Flowshop Scheduling Problem with Part of Jobs Subject to a Common Deadline Constraint
Qiuying Li, Quan-Ke Pan, Hongyan Sang, et al.
Expert Systems with Applications (2024) Vol. 248, pp. 123278-123278
Closed Access | Times Cited: 6
A hybrid estimation of distribution algorithm for solving assembly flexible job shop scheduling in a distributed environment
Baigang Du, Shuai Han, Jun Guo, et al.
Engineering Applications of Artificial Intelligence (2024) Vol. 133, pp. 108491-108491
Closed Access | Times Cited: 6
A bi-objective evolutionary algorithm for distributed production scheduling with eligibility restrictions
Chaoming Hu, Teng Zhang, Yao Gao, et al.
Applied Soft Computing (2025), pp. 112738-112738
Closed Access
Collaborative assembly factory in the distributed permutation flow-shop scheduling problem considering flexible assembly and fuzzy processing time
Long Cheng, Lei Wang, Jingcao Cai, et al.
Engineering Optimization (2025), pp. 1-32
Closed Access
An Optimization Problem of Distributed Permutation Flowshop Scheduling with an Order Acceptance Strategy in Heterogeneous Factories
Seungjae Lee, Byung Soo Kim
Mathematics (2025) Vol. 13, Iss. 5, pp. 877-877
Open Access
Supply chain-oriented permutation flowshop scheduling considering flexible assembly and setup times
Kuo‐Ching Ying, Pourya Pourhejazy, Chen-Yang Cheng, et al.
International Journal of Production Research (2020) Vol. 61, Iss. 1, pp. 258-281
Closed Access | Times Cited: 39
Integrated production and distribution scheduling in distributed hybrid flow shops
Hu Qin, Tao Li, Teng Yi, et al.
Memetic Computing (2021) Vol. 13, Iss. 2, pp. 185-202
Closed Access | Times Cited: 33
Q-learning-based multi-objective particle swarm optimization with local search within factories for energy-efficient distributed flow-shop scheduling problem
Wenqiang Zhang, Huili Geng, Chen Li, et al.
Journal of Intelligent Manufacturing (2023)
Closed Access | Times Cited: 12
Multi-resource constrained dynamic workshop scheduling based on proximal policy optimisation
Peng Luo, Huan Xiong, Bo Wen Zhang, et al.
International Journal of Production Research (2021) Vol. 60, Iss. 19, pp. 5937-5955
Closed Access | Times Cited: 27
Artificial intelligence as an enabler of quick and effective production repurposing: an exploratory review and future research propositions
Farheen Naz, Anil Kumar, Rohit Agrawal, et al.
Production Planning & Control (2023) Vol. 35, Iss. 16, pp. 2154-2177
Open Access | Times Cited: 11
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