An Exact Method for Solving the Multi-Processor Flow-Shop
RAIRO-Oper. Res., 34 1 (2000) 1-25
Published online: 2002-08-15
Articles citing this article
The Citing articles tool gives a list of articles citing the current article.
The citing articles come from EDP Sciences database, as well as other publishers participating in CrossRef Cited-by Linking Program. You can set up your personal account to receive an email alert each time this article is cited by a new article (see the menu on the right-hand side of the abstract page).
Cited article:
This article has been cited by the following article(s):
Selection hyperheuristic with knowledge-based Q-learning for dynamic distributed hybrid flow shop scheduling problem considering operation inspection
Lin Luo and Xuesong YanSwarm and Evolutionary Computation 95 101936 (2025)
https://doi.org/10.1016/j.swevo.2025.101936
A novel artificial intelligence search algorithm and mathematical model for the hybrid flow shop scheduling problem
Filip Vidojević, Andrijana Džamić, Dušan Džamić and Miroslav MarićJournal of Big Data 12 (1) (2025)
https://doi.org/10.1186/s40537-025-01085-x
Greedy-assisted teaching-learning-based optimization algorithm for cost-based hybrid flow shop scheduling
Wasif Ullah, Mohd Fadzil Faisae Ab Rashid and Muhammad Ammar Nik Mu’tasimExpert Systems with Applications 273 126955 (2025)
https://doi.org/10.1016/j.eswa.2025.126955
Modification of a Quantum-inspired Genetic Algorithm for Numerical Optimization Using Qudit under Conditions of Simulating Quantum Decoherence
Vladimir V. Maslennikov and Liliya A. DemidovaComputational nanotechnology 11 (2) 58 (2024)
https://doi.org/10.33693/2313-223X-2024-11-2-58-85
An improved co-evolutionary memetic algorithm based on novel schedule type and unconditional feasibility for hybrid flow-shop scheduling problem
Yue Teng, Xinyu Li, Liang Gao, Jin Xie and Yang LiComputers & Industrial Engineering 193 110324 (2024)
https://doi.org/10.1016/j.cie.2024.110324
Cost-based hybrid flow shop scheduling with uniform machine optimization using an improved tiki-taka algorithm
Mohd Fadzil Faisae Ab Rashid and Muhammad Ammar Nik Mu’tasimJournal of Industrial and Production Engineering 41 (2) 182 (2024)
https://doi.org/10.1080/21681015.2023.2276108
Theoretical analysis and implementation of mandatory operations-based accelerated search in graph space for hybrid flow shop scheduling
Yuting Wang, Yuyan Han, Huan Li, Junqing Li, Kaizhou Gao and Yiping LiuExpert Systems with Applications 257 125026 (2024)
https://doi.org/10.1016/j.eswa.2024.125026
A path relinking with tabu search algorithm for solving hybrid flow shop scheduling problem considering multiple critical paths
Hao Zhou, Hui Liu, Chang Lv, Chaoyong Zhang and Weiming ShenComputers & Operations Research 170 106783 (2024)
https://doi.org/10.1016/j.cor.2024.106783
Research on the scheduling of steel mesh production line based on the improved grey wolf algorithm
Haibin Yin, Yu Feng, Junyong Xie, Xiangqun Zhou, Yushun Zhang, Dongxing Shi and Zhongwei LiJournal of Physics: Conference Series 2787 (1) 012058 (2024)
https://doi.org/10.1088/1742-6596/2787/1/012058
850 419 (2024)
https://doi.org/10.1007/978-981-99-8819-8_34
A two-stage cross-neighborhood search algorithm bridging different solution representation spaces for solving the hybrid flow shop scheduling problem
Yuan Kuang, Xiuli Wu, Ziqi Chen and Wence LiSwarm and Evolutionary Computation 84 101455 (2024)
https://doi.org/10.1016/j.swevo.2023.101455
The application of heterogeneous graph neural network and deep reinforcement learning in hybrid flow shop scheduling problem
Yejian Zhao, Xiaochuan Luo and Yulin ZhangComputers & Industrial Engineering 187 109802 (2024)
https://doi.org/10.1016/j.cie.2023.109802
18 47 (2023)
https://doi.org/10.1007/978-981-99-6987-6_4
A systematic review of multi-objective hybrid flow shop scheduling
Janis S. Neufeld, Sven Schulz and Udo BuscherEuropean Journal of Operational Research 309 (1) 1 (2023)
https://doi.org/10.1016/j.ejor.2022.08.009
(2023)
https://doi.org/10.2139/ssrn.4600335
A Hybrid Evolutionary Algorithm Using Two Solution Representations for Hybrid Flow-Shop Scheduling Problem
Jiaxin Fan, Yingli Li, Jin Xie, Chunjiang Zhang, Weiming Shen and Liang GaoIEEE Transactions on Cybernetics 53 (3) 1752 (2023)
https://doi.org/10.1109/TCYB.2021.3120875
(2023)
https://doi.org/10.2139/ssrn.4679406
Multi-Objective Hybrid Flow-Shop Scheduling in Parallel Sequential Mode While Considering Handling Time and Setup Time
Yingjie Feng and Jili KongApplied Sciences 13 (6) 3563 (2023)
https://doi.org/10.3390/app13063563
Research on Production Scheduling Technology in Knitting Workshop Based on Improved Genetic Algorithm
Lei Sun, Weimin Shi, Junru Wang, et al.Applied Sciences 13 (9) 5701 (2023)
https://doi.org/10.3390/app13095701
An Evaluation of Mathematical Programming and Lower-Bound Methods for Hybrid Flow Shop Problems With a Makespan Criterion
Yarong Chen, Ya-Chih Tsai and Fuh-Der ChouIEEE Access 11 41368 (2023)
https://doi.org/10.1109/ACCESS.2023.3268214
Constraint programming models for the hybrid flow shop scheduling problem and its extensions
Eyüp Ensar Işık, Seyda Topaloglu Yildiz and Özge Şatır AkpunarSoft Computing 27 (24) 18623 (2023)
https://doi.org/10.1007/s00500-023-09086-9
Digital Transformation in Industry
Luca Fumagalli, Elisa Negri, Laura Cattaneo, Lorenzo Ragazzini and Marco MacchiLecture Notes in Information Systems and Organisation, Digital Transformation in Industry 61 267 (2023)
https://doi.org/10.1007/978-3-031-30351-7_21
(2023)
https://doi.org/10.2139/ssrn.4600334
1176 (2022)
https://doi.org/10.1109/CVIDLICCEA56201.2022.9824804
Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation
Meral İşler and Orhan EnginLecture Notes in Networks and Systems, Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation 307 623 (2022)
https://doi.org/10.1007/978-3-030-85626-7_73
395 (2022)
https://doi.org/10.1109/CoST57098.2022.00087
488 (2022)
https://doi.org/10.1109/MDM55031.2022.00104
Recent Advances in Computational Optimization
Natalia GrigorevaStudies in Computational Intelligence, Recent Advances in Computational Optimization 986 139 (2022)
https://doi.org/10.1007/978-3-030-82397-9_7
1 (2022)
https://doi.org/10.1109/ICNSC55942.2022.10004154
New benchmark algorithm for hybrid flowshop scheduling with identical machines
Shih-Wei Lin, Chen-Yang Cheng, Pourya Pourhejazy, Kuo-Ching Ying and Chia-Hui LeeExpert Systems with Applications 183 115422 (2021)
https://doi.org/10.1016/j.eswa.2021.115422
Improved SP-MCTS-Based Scheduling for Multi-Constraint Hybrid Flow Shop
Jian Guo, Yaoyao Shi, Zhen Chen, Tao Yu, Bijan Shirinzadeh and Pan ZhaoApplied Sciences 10 (18) 6220 (2020)
https://doi.org/10.3390/app10186220
A hybrid multi-objective artificial bee colony algorithm for flexible task scheduling problems in cloud computing system
Jun-qing Li and Yun-qi HanCluster Computing 23 (4) 2483 (2020)
https://doi.org/10.1007/s10586-019-03022-z
Memetic algorithm for solving flexible flow-shop scheduling problems with dynamic transport waiting times
Chuanjin Lei, Ning Zhao, Song Ye and Xiuli WuComputers & Industrial Engineering 139 105984 (2020)
https://doi.org/10.1016/j.cie.2019.07.041
Design of a testbed for hybrid flow shop scheduling with identical machines
Victor Fernandez-Viagas and Jose M. FraminanComputers & Industrial Engineering 141 106288 (2020)
https://doi.org/10.1016/j.cie.2020.106288
Ensemble of metaheuristics for energy-efficient hybrid flowshops: Makespan versus total energy consumption
Hande Öztop, M. Fatih Tasgetiren, Levent Kandiller, Deniz Türsel Eliiyi and Liang GaoSwarm and Evolutionary Computation 54 100660 (2020)
https://doi.org/10.1016/j.swevo.2020.100660
36 (2020)
https://doi.org/10.1109/ISCAIE47305.2020.9108829
Research on Multi-Objective Hybrid Flow Shop Scheduling Problem With Dual Resource Constraints Using Improved Memetic Algorithm
Kaifeng Geng, Chunming Ye and Li LiuIEEE Access 8 104527 (2020)
https://doi.org/10.1109/ACCESS.2020.2999680
Automatic Algorithm Design for Hybrid Flowshop Scheduling Problems
Pedro Alfaro-Fernández, Rubén Ruiz, Federico Pagnozzi and Thomas StützleEuropean Journal of Operational Research 282 (3) 835 (2020)
https://doi.org/10.1016/j.ejor.2019.10.004
A multiobjective evolutionary algorithm based on decomposition for hybrid flowshop green scheduling problem
Biao Zhang, Quan-ke Pan, Liang Gao, et al.Computers & Industrial Engineering 136 325 (2019)
https://doi.org/10.1016/j.cie.2019.07.036
A multi-objective migrating birds optimization algorithm for the hybrid flowshop rescheduling problem
Biao Zhang, Quan-ke Pan, Liang Gao, Xin-li Zhang and Kun-kun PengSoft Computing 23 (17) 8101 (2019)
https://doi.org/10.1007/s00500-018-3447-8
Efficiency of the solution representations for the hybrid flow shop scheduling problem with makespan objective
Victor Fernandez-Viagas, Paz Perez-Gonzalez and Jose M. FraminanComputers & Operations Research 109 77 (2019)
https://doi.org/10.1016/j.cor.2019.05.002
Flexible Flow Shop Scheduling Method with Public Buffer
Zhonghua Han, Chao Han, Shuo Lin, Xiaoting Dong and Haibo ShiProcesses 7 (10) 681 (2019)
https://doi.org/10.3390/pr7100681
A multi-objective cellular grey wolf optimizer for hybrid flowshop scheduling problem considering noise pollution
Chao Lu, Liang Gao, Quanke Pan, Xinyu Li and Jun ZhengApplied Soft Computing 75 728 (2019)
https://doi.org/10.1016/j.asoc.2018.11.043
Metaheuristic algorithms for the hybrid flowshop scheduling problem
Hande Öztop, M. Fatih Tasgetiren, Deniz Türsel Eliiyi and Quan-Ke PanComputers & Operations Research 111 177 (2019)
https://doi.org/10.1016/j.cor.2019.06.009
Critical Developments and Applications of Swarm Intelligence
M. K. Marichelvam and Ömür TosunAdvances in Computational Intelligence and Robotics, Critical Developments and Applications of Swarm Intelligence 379 (2018)
https://doi.org/10.4018/978-1-5225-5134-8.ch015
Efficient multi-objective optimization algorithm for hybrid flow shop scheduling problems with setup energy consumptions
Jun-qing Li, Hong-yan Sang, Yu-yan Han, Cun-gang Wang and Kai-zhou GaoJournal of Cleaner Production 181 584 (2018)
https://doi.org/10.1016/j.jclepro.2018.02.004
Efficient heuristics for the hybrid flow shop scheduling problem with missing operations
Manuel Dios, Victor Fernandez-Viagas and Jose M. FraminanComputers & Industrial Engineering 115 88 (2018)
https://doi.org/10.1016/j.cie.2017.10.034
New efficient constructive heuristics for the hybrid flowshop to minimise makespan: A computational evaluation of heuristics
Victor Fernandez-Viagas, Jose M. Molina-Pariente and Jose M. FraminanExpert Systems with Applications 114 345 (2018)
https://doi.org/10.1016/j.eswa.2018.07.055
379 (2018)
https://doi.org/10.1145/3205455.3205500
1 (2018)
https://doi.org/10.1109/ICMIC.2018.8529921
Improved teaching–learning-based and JAYA optimization algorithms for solving flexible flow shop scheduling problems
Raviteja Buddala and Siba Sankar MahapatraJournal of Industrial Engineering International 14 (3) 555 (2018)
https://doi.org/10.1007/s40092-017-0244-4
181 (2017)
https://doi.org/10.1109/ICMIC.2017.8321635
930 (2017)
https://doi.org/10.1109/FSKD.2017.8393402
An effective modified migrating birds optimization for hybrid flowshop scheduling problem with lot streaming
Biao Zhang, Quan-ke Pan, Liang Gao, Xin-li Zhang, Hong-yan Sang and Jun-qing LiApplied Soft Computing 52 14 (2017)
https://doi.org/10.1016/j.asoc.2016.12.021
169 (2017)
https://doi.org/10.1109/ICMIC.2017.8321633
Production-inventory-routing coordination with capacity and time window constraints for perishable products: Heuristic and meta-heuristic algorithms
Behnam Vahdani, S.T.A. Niaki and S. AslanzadeJournal of Cleaner Production 161 598 (2017)
https://doi.org/10.1016/j.jclepro.2017.05.113
233 (2016)
https://doi.org/10.1109/CSCWD.2016.7565994
Information Systems Architecture and Technology: Proceedings of 36th International Conference on Information Systems Architecture and Technology – ISAT 2015 – Part I
Jarosław WikarekAdvances in Intelligent Systems and Computing, Information Systems Architecture and Technology: Proceedings of 36th International Conference on Information Systems Architecture and Technology – ISAT 2015 – Part I 429 53 (2016)
https://doi.org/10.1007/978-3-319-28555-9_5
An improved discrete artificial bee colony algorithm to minimize the makespan on hybrid flow shop problems
Zhe Cui and Xingsheng GuNeurocomputing 148 248 (2015)
https://doi.org/10.1016/j.neucom.2013.07.056
A Survey on Occurrence of Critical Machines in a Manufacturing Environment
R. Pugazhenthi and M. Anthony XaviorProcedia Engineering 97 105 (2014)
https://doi.org/10.1016/j.proeng.2014.12.230
Hybrid Particle Swarm Optimization for Hybrid Flowshop Scheduling Problem with Maintenance Activities
Jun-qing Li, Quan-ke Pan and Kun MaoThe Scientific World Journal 2014 1 (2014)
https://doi.org/10.1155/2014/596850
16 (2014)
https://doi.org/10.1109/CIPLS.2014.7007156
A novel genetic algorithm for the hybrid flow shop scheduling with parallel batching and eligibility constraints
Antonio Costa, Fulvio Antonio Cappadonna and Sergio FicheraThe International Journal of Advanced Manufacturing Technology 75 (5-8) 833 (2014)
https://doi.org/10.1007/s00170-014-6195-7
A hybrid variable neighborhood search for solving the hybrid flow shop scheduling problem
Jun-qing Li, Quan-ke Pan and Fa-tao WangApplied Soft Computing 24 63 (2014)
https://doi.org/10.1016/j.asoc.2014.07.005
A novel discrete artificial bee colony algorithm for the hybrid flowshop scheduling problem with makespan minimisation
Quan-Ke Pan, Ling Wang, Jun-Qing Li and Jun-Hua DuanOmega 45 42 (2014)
https://doi.org/10.1016/j.omega.2013.12.004
An improved migrating birds optimisation for a hybrid flowshop scheduling with total flowtime minimisation
Quan-Ke Pan and Yan DongInformation Sciences 277 643 (2014)
https://doi.org/10.1016/j.ins.2014.02.152
Three-stage hybrid-flowshop model for cross-docking
Adrien Bellanger, Saïd Hanafi and Christophe WilbautComputers & Operations Research 40 (4) 1109 (2013)
https://doi.org/10.1016/j.cor.2012.11.009
Trends in Developing Metaheuristics, Algorithms, and Optimization Approaches
Safa Khalouli, Fatima Ghedjati and Abdelaziz HamzaouiTrends in Developing Metaheuristics, Algorithms, and Optimization Approaches 85 (2013)
https://doi.org/10.4018/978-1-4666-2145-9.ch006
An effective shuffled frog-leaping algorithm for solving the hybrid flow-shop scheduling problem with identical parallel machines
Ye Xu, Ling Wang, Shengyao Wang and Min LiuEngineering Optimization 45 (12) 1409 (2013)
https://doi.org/10.1080/0305215X.2012.737784
An immunoglobulin-based artificial immune system for solving the hybrid flow shop problem
Tsui-Ping Chung and Ching-Jong LiaoApplied Soft Computing 13 (8) 3729 (2013)
https://doi.org/10.1016/j.asoc.2013.03.006
An enhanced estimation of distribution algorithm for solving hybrid flow-shop scheduling problem with identical parallel machines
Sheng-yao Wang, Ling Wang, Min Liu and Ye XuThe International Journal of Advanced Manufacturing Technology 68 (9-12) 2043 (2013)
https://doi.org/10.1007/s00170-013-4819-y
Intelligent Computing for Sustainable Energy and Environment
Zhe Cui and Xingsheng GuCommunications in Computer and Information Science, Intelligent Computing for Sustainable Energy and Environment 355 294 (2013)
https://doi.org/10.1007/978-3-642-37105-9_33
Taking advantage of a diverse set of efficient production schedules: A two-step approach for scheduling with side concerns
Selçuk Gören and Henri PierrevalComputers & Operations Research 40 (8) 1979 (2013)
https://doi.org/10.1016/j.cor.2013.02.016
An approach using particle swarm optimization and bottleneck heuristic to solve hybrid flow shop scheduling problem
Ching-Jong Liao, Evi Tjandradjaja and Tsui-Ping ChungApplied Soft Computing 12 (6) 1755 (2012)
https://doi.org/10.1016/j.asoc.2012.01.011
An Ant Colony System Algorithm for the Hybrid Flow-Shop Scheduling Problem
Safa Khalouli, Fatima Ghedjati and Abdelaziz HamzaouiInternational Journal of Applied Metaheuristic Computing 2 (1) 29 (2011)
https://doi.org/10.4018/jamc.2011010103
Bounding strategies for the hybrid flow shop scheduling problem
Lotfi Hidri and Mohamed HaouariApplied Mathematics and Computation 217 (21) 8248 (2011)
https://doi.org/10.1016/j.amc.2011.02.108
The hybrid flow shop scheduling problem
Rubén Ruiz and José Antonio Vázquez-RodríguezEuropean Journal of Operational Research 205 (1) 1 (2010)
https://doi.org/10.1016/j.ejor.2009.09.024
Review and classification of hybrid flow shop scheduling problems from a production system and a solutions procedure perspective
Imma Ribas, Rainer Leisten and Jose M. FramiñanComputers & Operations Research 37 (8) 1439 (2010)
https://doi.org/10.1016/j.cor.2009.11.001
1 (2009)
https://doi.org/10.1109/ICMSS.2009.5301354
Hybrid Flow-Shop: a Memetic Algorithm Using Constraint-Based Scheduling for Efficient Search
Antoine Jouglet, Ceyda Oğuz and Marc SevauxJournal of Mathematical Modelling and Algorithms 8 (3) 271 (2009)
https://doi.org/10.1007/s10852-008-9101-1
1873 (2009)
https://doi.org/10.1109/CEC.2009.4983169
554 (2009)
https://doi.org/10.1109/ICCIE.2009.5223779
A taxonomy of flexible flow line scheduling procedures
Daniel Quadt and Heinrich KuhnEuropean Journal of Operational Research 178 (3) 686 (2007)
https://doi.org/10.1016/j.ejor.2006.01.042
3776 (2007)
https://doi.org/10.1109/CEC.2007.4424962
Using ant colony optimization to solve hybrid flow shop scheduling problems
Kemal Alaykýran, Orhan Engin and Alper DöyenThe International Journal of Advanced Manufacturing Technology 35 (5-6) 541 (2007)
https://doi.org/10.1007/s00170-007-1048-2
An approximate decomposition algorithm for scheduling on parallel machines with heads and tails
Anis Gharbi and Mohamed HaouariComputers & Operations Research 34 (3) 868 (2007)
https://doi.org/10.1016/j.cor.2005.05.012
Handbook on Scheduling
International Handbook on Information Systems, Handbook on Scheduling 271 (2007)https://doi.org/10.1007/978-3-540-32220-7_8
1120 (2006)
https://doi.org/10.1109/ICSSSM.2006.320665
Optimal Scheduling of a Two-stage Hybrid Flow Shop
Mohamed Haouari, Lotfi Hidri and Anis GharbiMathematical Methods of Operations Research 64 (1) 107 (2006)
https://doi.org/10.1007/s00186-006-0066-4
A review of exact solution methods for the non-preemptive multiprocessor flowshop problem
Tamás Kis and Erwin PeschEuropean Journal of Operational Research 164 (3) 592 (2005)
https://doi.org/10.1016/j.ejor.2003.12.026
Schedule Generation Schemes for the Job-Shop Problem with Sequence-Dependent Setup Times: Dominance Properties and Computational Analysis
Christian Artigues, Pierre Lopez and Pierre-Dimitri AyacheAnnals of Operations Research 138 (1) 21 (2005)
https://doi.org/10.1007/s10479-005-2443-4
Optimal parallel machines scheduling with availability constraints
Anis Gharbi and Mohamed HaouariDiscrete Applied Mathematics 148 (1) 63 (2005)
https://doi.org/10.1016/j.dam.2004.12.003
Practice and Theory of Automated Timetabling III
Peter Brucker and Sigrid KnustLecture Notes in Computer Science, Practice and Theory of Automated Timetabling III 2079 277 (2001)
https://doi.org/10.1007/3-540-44629-X_17
List scheduling in a parallel machine environment with precedence constraints and setup times
Johann Hurink and Sigrid KnustOperations Research Letters 29 (5) 231 (2001)
https://doi.org/10.1016/S0167-6377(01)00104-3