Advanced search
Publication Cover
International Journal of Production Research Volume 50, 2012 - Issue 15
Submit an article Journal homepage
1,507
Views
106
CrossRef citations to date
0
Altmetric
Original Articles

A comparison of priority rules for the job shop scheduling problem under different flow time- and tardiness-related objective functions

Veronique Sels Faculty of Economics and Business Administration, Ghent University, Tweekerkenstraat 2, 9000 Gent, BelgiumCorrespondence[email protected]
,
Nele Gheysen Faculty of Economics and Business Administration, Ghent University, Tweekerkenstraat 2, 9000 Gent, Belgium
&
Mario Vanhoucke Faculty of Economics and Business Administration, Ghent University, Tweekerkenstraat 2, 9000 Gent, Belgium; Operations and Technology Management Centre, Vlerick Leuven Gent Management School, Reep 1, 9000 Gent, Belgium; Department of Management Science and Innovation, University College London, Gower Street, London WC1E 6BT, UK
Pages 4255-4270 | Received 06 Oct 2010, Accepted 07 Jul 2011, Published online: 07 Sep 2011

Citations (106)

Keep up to date with the latest research on this topic with citation updates for this article.

Subscribe to citation updates

Read on this site (9)

Xavier Delorme, Gérard Fleury, Philippe Lacomme & Damien Lamy. (2024) Modelling and solving approaches for scheduling problems in reconfigurable manufacturing systems. International Journal of Production Research 62:7, pages 2683-2704.
Read now
M. Thenarasu, K. Rameshkumar, M. Di Mascolo & S.P. Anbuudayasankar. (2024) Multi-criteria scheduling of realistic flexible job shop: a novel approach for integrating simulation modelling and multi-criteria decision making. International Journal of Production Research 62:1-2, pages 336-358.
Read now
Salama Shady, Toshiya Kaihara, Nobutada Fujii & Daisuke Kokuryo. (2023) Feature selection approach for evolving reactive scheduling policies for dynamic job shop scheduling problem using gene expression programming. International Journal of Production Research 61:15, pages 5029-5052.
Read now
Renke Liu, Rajesh Piplani & Carlos Toro. (2022) Deep reinforcement learning for dynamic scheduling of a flexible job shop. International Journal of Production Research 60:13, pages 4049-4069.
Read now
Salama Shady, Toshiya Kaihara, Nobutada Fujii & Daisuke Kokuryo. (2022) A novel feature selection for evolving compact dispatching rules using genetic programming for dynamic job shop scheduling. International Journal of Production Research 60:13, pages 4025-4048.
Read now
Ghorbanali Mohammadi & Erfan Moaddabi. (2021) Using two metaheuristic algorithms for scheduling parallel machines with sequence dependent set-up times in job shop industries. International Journal of Systems Science 52:14, pages 2904-2917.
Read now
Gurkan Ozturk, Ozan Bahadir & Aydin Teymourifar. (2019) Extracting priority rules for dynamic multi-objective flexible job shop scheduling problems using gene expression programming. International Journal of Production Research 57:10, pages 3121-3137.
Read now
Durk-Jouke van der Zee. (2017) Coordinating batching decisions in manufacturing networks. International Journal of Production Research 55:18, pages 5405-5422.
Read now
Gabriel Zambrano Rey, Abdelghani Bekrar, Vittaldas Prabhu & Damien Trentesaux. (2014) Coupling a genetic algorithm with the distributed arrival-time control for the JIT dynamic scheduling of flexible job-shops. International Journal of Production Research 52:12, pages 3688-3709.
Read now

Articles from other publishers (97)

Xinquan Wu, Xuefeng Yan, Donghai Guan & Mingqiang Wei. (2024) A deep reinforcement learning model for dynamic job-shop scheduling problem with uncertain processing time. Engineering Applications of Artificial Intelligence 131, pages 107790.
Crossref
Yu Pu, Fang Li & Shahin Rahimifard. (2024) Multi-Agent Reinforcement Learning for Job Shop Scheduling in Dynamic Environments. Sustainability 16:8, pages 3234.
Crossref
Runqing Wang, Gang Wang, Jian Sun, Fang Deng & Jie Chen. (2024) Flexible Job Shop Scheduling via Dual Attention Network-Based Reinforcement Learning. IEEE Transactions on Neural Networks and Learning Systems 35:3, pages 3091-3102.
Crossref
Jiang-Ping Huang, Liang Gao & Xin-Yu Li. (2024) An end-to-end deep reinforcement learning method based on graph neural network for distributed job-shop scheduling problem. Expert Systems with Applications 238, pages 121756.
Crossref
Yu-Hung Chang, Chien-Hung Liu & Shingchern D. You. (2024) Scheduling for the Flexible Job-Shop Problem with a Dynamic Number of Machines Using Deep Reinforcement Learning. Information 15:2, pages 82.
Crossref
Eiji Morinaga, Xuetian Tang, Koji Iwamura & Naoki Hirabayashi. (2024) Improvement of job shop scheduling method based on mathematical optimization and machine learning. Procedia Computer Science 232, pages 871-879.
Crossref
Francisco J. Gil-Gala, María R. Sierra, Carlos Mencía & Ramiro Varela. (2023) Surrogate model for memetic genetic programming with application to the one machine scheduling problem with time-varying capacity. Expert Systems with Applications 233, pages 120916.
Crossref
Xinquan Wu & Xuefeng Yan. (2023) A spatial pyramid pooling-based deep reinforcement learning model for dynamic job-shop scheduling problem. Computers & Operations Research 160, pages 106401.
Crossref
Renke Liu, Rajesh Piplani & Carlos Toro. (2023) A deep multi-agent reinforcement learning approach to solve dynamic job shop scheduling problem. Computers & Operations Research 159, pages 106294.
Crossref
Jiang-Ping Huang, Liang Gao, Xin-Yu Li & Chun-Jiang Zhang. (2023) A cooperative hierarchical deep reinforcement learning based multi-agent method for distributed job shop scheduling problem with random job arrivals. Computers & Industrial Engineering 185, pages 109650.
Crossref
Sirui Chen, Yuming Tian & Lingling An. (2023) Multi-Objective Order Scheduling via Reinforcement Learning. Algorithms 16:11, pages 495.
Crossref
Yuxuan Deng, Lianglun Cheng & Tao Wang. (2023) Distributed Real-Time Workflow Scheduling for Collaborative Operation of Heterogeneous Industrial Equipment. Distributed Real-Time Workflow Scheduling for Collaborative Operation of Heterogeneous Industrial Equipment.
Zexiang Shi & Zhibin Chen. (2023) On algorithms for JSSP based on hybrid graph neural network. On algorithms for JSSP based on hybrid graph neural network.
Hao Wang, Tao Peng, Aydin Nassehi & Renzhong Tang. (2023) A data-driven simulation-optimization framework for generating priority dispatching rules in dynamic job shop scheduling with uncertainties. Journal of Manufacturing Systems 70, pages 288-308.
Crossref
Anran Zhao, Peng Liu, Yunfeng Li, Zheyu Xie, Longhao Hu & Haoyuan Li. (2023) Real-Time Selection System of Dispatching Rules for the Job Shop Scheduling Problem. Machines 11:10, pages 921.
Crossref
Chupeng Su, Cong Zhang, Dan Xia, Baoan Han, Chuang Wang, Gang Chen & Longhan Xie. (2023) Evolution strategies-based optimized graph reinforcement learning for solving dynamic job shop scheduling problem. Applied Soft Computing 145, pages 110596.
Crossref
Jiang-Ping Huang, Liang Gao, Xin-Yu Li & Chun-Jiang Zhang. (2023) A novel priority dispatch rule generation method based on graph neural network and reinforcement learning for distributed job-shop scheduling. Journal of Manufacturing Systems 69, pages 119-134.
Crossref
Rojin Nekoueian, Tom Servranckx & Mario Vanhoucke. (2023) Constructive heuristics for selecting and scheduling alternative subgraphs in resource-constrained projects. Computers & Industrial Engineering 182, pages 109399.
Crossref
Huijuan Ma, Xiang Huang, Zhili Hu, Yizhe Chen, Dongsheng Qian, Jiadong Deng & Lin Hua. (2023) Multi-objective production scheduling optimization and management control system of complex aerospace components: a review. The International Journal of Advanced Manufacturing Technology 127:11-12, pages 4973-4993.
Crossref
Kuo-Hao Ho, Ji-Han Wu, Fan Chiang, Yuan-Yu Wu, Sheng-I Chen, Ted Kuo, Feng-Jian Wang & I-Chen Wu. (2023) Deep Reinforcement Learning Based on Graph Neural Networks for Job-shop Scheduling. Deep Reinforcement Learning Based on Graph Neural Networks for Job-shop Scheduling.
Ali Fırat İnal, Çağrı Sel, Adnan Aktepe, Ahmet Kürşad Türker & Süleyman Ersöz. (2023) A Multi-Agent Reinforcement Learning Approach to the Dynamic Job Shop Scheduling Problem. Sustainability 15:10, pages 8262.
Crossref
Tao Xu, Kai Xu, Jiangming Zhang, Sijie Yang & Junjie Huang. (2023) Quality Inspection Scheduling Problem Based on Reinforcement Learning Environment. Quality Inspection Scheduling Problem Based on Reinforcement Learning Environment.
Cong Zhang, Yaoxin Wu, Yining Ma, Wen Song, Zhang Le, Zhiguang Cao & Jie Zhang. (2023) A review on learning to solve combinatorial optimisation problems in manufacturing. IET Collaborative Intelligent Manufacturing 5:1.
Crossref
Eiji MORINAGA, Kenta TERAMOTOHidefumi WAKAMATSU. (2023) Method of job shop scheduling considering reworking and reprocessing based on proactive approach. Journal of Advanced Mechanical Design, Systems, and Manufacturing 17:1, pages JAMDSM0013-JAMDSM0013.
Crossref
Eiji Morinaga, Xuetian Tang, Koji Iwamura & Naoki Hirabayashi. (2023) An improved method of job shop scheduling using machine learning and mathematical optimization. Procedia Computer Science 217, pages 1479-1486.
Crossref
Giovanni Bonetta, Davide Zago, Rossella Cancelliere & Andrea Grosso. 2023. Learning and Intelligent Optimization. Learning and Intelligent Optimization 475 490 .
Eiji Morinaga, Kenta Teramoto & Hidefumi Wakamatsu. 2023. Advances in Production Management Systems. Production Management Systems for Responsible Manufacturing, Service, and Logistics Futures. Advances in Production Management Systems. Production Management Systems for Responsible Manufacturing, Service, and Logistics Futures 576 590 .
Alexander Kinast, Roland Braune, Karl F. Doerner & Stefanie Rinderle-Ma. 2023. Business Process Management Forum. Business Process Management Forum 232 248 .
Jonas K. Falkner, Daniela Thyssens, Ahmad Bdeir & Lars Schmidt-Thieme. 2023. Machine Learning and Knowledge Discovery in Databases. Machine Learning and Knowledge Discovery in Databases 361 376 .
Anran Zhao, Peng Liu, Xiyu Gao, Guotai Huang, Xiuguang Yang, Yuan Ma, Zheyu Xie & Yunfeng Li. (2022) Data-Mining-Based Real-Time Optimization of the Job Shop Scheduling Problem. Mathematics 10:23, pages 4608.
Crossref
Zhenran Kuai, Tianyu Wang & Shaowei Wang. (2022) Fair Virtual Network Function Mapping and Scheduling Using Proximal Policy Optimization. IEEE Transactions on Communications 70:11, pages 7434-7445.
Crossref
Shu Luo, Linxuan Zhang & Yushun Fan. (2022) Real-Time Scheduling for Dynamic Partial-No-Wait Multiobjective Flexible Job Shop by Deep Reinforcement Learning. IEEE Transactions on Automation Science and Engineering 19:4, pages 3020-3038.
Crossref
Atiya Masood, Gang Chen, Yi Mei, Harith Al-Sahaf & Mengjie Zhang. (2022) Genetic Programming Hyper-heuristic with Gaussian Process-based Reference Point Adaption for Many-Objective Job Shop Scheduling. Genetic Programming Hyper-heuristic with Gaussian Process-based Reference Point Adaption for Many-Objective Job Shop Scheduling.
Saydul Akbar Murad, Abu Jafar Md Muzahid, Zafril Rizal M Azmi, Md Imdadul Hoque & Md Kowsher. (2022) A review on job scheduling technique in cloud computing and priority rule based intelligent framework. Journal of King Saud University - Computer and Information Sciences 34:6, pages 2309-2331.
Crossref
Amar Oukil, Ahmed El-Bouri & Ali Emrouznejad. (2022) Energy-aware job scheduling in a multi-objective production environment – An integrated DEA-OWA model. Computers & Industrial Engineering 168, pages 108065.
Crossref
Anran Zhao, Peng Liu, Guotai Huang, Xiyu Gao, Xiuguang Yang, Yunfeng Li & Yuan Ma. (2022) Model for Selecting Optimal Dispatching Rules Based Real-time Optimize Job Shop Scheduling Problem. Mathematical Problems in Engineering 2022, pages 1-14.
Crossref
Shady Salama, Toshiya Kaihara, Nobutada Fujii & Daisuke Kokuryo. (2022) Multi-Objective Approach with a Distance Metric in Genetic Programming for Job Shop Scheduling. International Journal of Automation Technology 16:3, pages 296-308.
Crossref
Alper Türkyılmaz, Ozlem Senvar, İrem Ünal & Serol Bulkan. (2022) A hybrid genetic algorithm based on a two-level hypervolume contribution measure selection strategy for bi-objective flexible job shop problem. Computers & Operations Research 141, pages 105694.
Crossref
Wei Weng, Junru Chen, Meimei Zheng & Shigeru Fujimura. (2022) Realtime scheduling heuristics for just-in-time production in large-scale flexible job shops. Journal of Manufacturing Systems 63, pages 64-77.
Crossref
Mehdy Morady Gohareh & Ehsan Mansouri. (2022) A simulation-optimization framework for generating dynamic dispatching rules for stochastic job shop with earliness and tardiness penalties. Computers & Operations Research 140, pages 105650.
Crossref
M. Thenarasu, K. Rameshkumar, Jacob Rousseau & S.P. Anbuudayasankar. (2022) Development and analysis of priority decision rules using MCDM approach for a flexible job shop scheduling: A simulation study. Simulation Modelling Practice and Theory 114, pages 102416.
Crossref
Roland Braune, Frank Benda, Karl F. Doerner & Richard F. Hartl. (2022) A genetic programming learning approach to generate dispatching rules for flexible shop scheduling problems. International Journal of Production Economics 243, pages 108342.
Crossref
Ragazzini Lorenzo, Negri Elisa & Macchi Marco. (2022) Local Digital Twin-based control of a cobot-assisted assembly cell based on Dispatching Rules. IFAC-PapersOnLine 55:2, pages 372-377.
Crossref
S. Ashwin, V. Shankaranarayanan, Damien lamy, S. P. Anbuudayasankar & M. Thenarasu. 2022. Intelligent Manufacturing and Energy Sustainability. Intelligent Manufacturing and Energy Sustainability 337 345 .
Sai Panda, Yi Mei & Mengjie Zhang. 2022. Evolutionary Computation in Combinatorial Optimization. Evolutionary Computation in Combinatorial Optimization 95 110 .
Christian Klanke, Vassilios Yfantis, Francesc Corominas & Sebastian Engell. (2021) Short-term scheduling of make-and-pack processes in the consumer goods industry using discrete-time and precedence-based MILP models. Computers & Chemical Engineering 154, pages 107453.
Crossref
Divya V & Leena Sri R. (2021) Fault tolerant resource allocation in fog environment using game theory‐based reinforcement learning. Concurrency and Computation: Practice and Experience 33:16.
Crossref
Jian Zhang, Tingming Deng, Haifan Jiang, Haojie Chen, Shengfeng Qin & Guofu Ding. (2021) Bi-level dynamic scheduling architecture based on service unit digital twin agents. Journal of Manufacturing Systems 60, pages 59-79.
Crossref
Sai Panda & Yi Mei. (2021) Genetic Programming with Algebraic Simplification for Dynamic Job Shop Scheduling. Genetic Programming with Algebraic Simplification for Dynamic Job Shop Scheduling.
David Garcia, Houda Tlahig, Belgacem Bettayeb & M'hammed Sahnoun. (2021) Evaluation of Dispatching Rules Performance for a DJSSP: Towards their Application in Industry 4.0. Evaluation of Dispatching Rules Performance for a DJSSP: Towards their Application in Industry 4.0.
Shiyong Wang, Yu Ou, Zhuohao Li, Yongjun Cao & Jiafu Wan. (2021) Simulation Optimization of the Prototype for Hybrid Production of Multi-Type Products. Simulation Optimization of the Prototype for Hybrid Production of Multi-Type Products.
Zuzana Červeňanská, Pavel Važan, Martin Juhás & Bohuslava Juhásová. (2021) Multi-Criteria Optimization in Operations Scheduling Applying Selected Priority Rules. Applied Sciences 11:6, pages 2783.
Crossref
Su Nguyen, Mengjie Zhang, Damminda Alahakoon & Kay Chen Tan. (2021) People-Centric Evolutionary System for Dynamic Production Scheduling. IEEE Transactions on Cybernetics 51:3, pages 1403-1416.
Crossref
Salama Shady, Toshiya Kaihara, Nobutada Fujii & Daisuke Kokuryo. (2021) Evolving Dispatching Rules Using Genetic Programming for Multi-objective Dynamic Job Shop Scheduling with Machine Breakdowns. Procedia CIRP 104, pages 411-416.
Crossref
Trang Hong Son, Tran Van Lang, Nguyen Huynh-Tuong & Ameur Soukhal. (2020) Resolution for bounded-splitting jobs scheduling problem on a single machine in available time-windows. Journal of Ambient Intelligence and Humanized Computing 12:1, pages 1179-1196.
Crossref
Liu Renke, Rajesh Piplani & Carlos Toro. 2021. Implementing Industry 4.0. Implementing Industry 4.0 229 258 .
M. H. Sim, M. Y. H. Low, C. S. Chong & M. Shakeri. (2020) Job Shop Scheduling Problem Neural Network Solver with Dispatching Rules. Job Shop Scheduling Problem Neural Network Solver with Dispatching Rules.
Hanyang Li, Chao Wang, Sheng Jiang, Sheng Liu, Yiming Rong & Xuekun Li. (2020) The study of intelligent scheduling algorithm oriented to complex constraints and multi-process roller grinding workshop. Advances in Mechanical Engineering 12:11, pages 168781402097588.
Crossref
Wei Weng, Junru Chen, Meimei Zheng & Shigeru Fujimura. (2020) Production Control Methods for Time-based Manufacturing in a Real Factory. Production Control Methods for Time-based Manufacturing in a Real Factory.
Atiya Masood, Gang Chen, Yi Mei, Harith Al-Sahaf & Mengjie Zhang. (2020) A Fitness-based Selection Method for Pareto Local Search for Many-Objective Job Shop Scheduling. A Fitness-based Selection Method for Pareto Local Search for Many-Objective Job Shop Scheduling.
R. Leena Sri & V. Divya. 2020. Energy Efficiency of Medical Devices and Healthcare Applications. Energy Efficiency of Medical Devices and Healthcare Applications 87 107 .
Salama Shady, Toshiya Kaihara, Nobutada Fujii & Daisuke Kokuryo. 2020. Advances in Production Management Systems. The Path to Digital Transformation and Innovation of Production Management Systems. Advances in Production Management Systems. The Path to Digital Transformation and Innovation of Production Management Systems 399 407 .
Kevin D. Sweeney, Donald C. SweeneyIIII & James F. Campbell. (2019) The performance of priority dispatching rules in a complex job shop: A study on the Upper Mississippi River. International Journal of Production Economics 216, pages 154-172.
Crossref
Su Nguyen, Yi Mei, Bing Xue & Mengjie Zhang. (2019) A Hybrid Genetic Programming Algorithm for Automated Design of Dispatching Rules. Evolutionary Computation 27:3, pages 467-496.
Crossref
Alessandro Brusaferri, Egidio Leo, Leonardo Nicolosi, Danial Ramin & Stefano Spinelli. (2019) Integrated automation system with PSO based scheduling for PCB remanufacturing plants. Integrated automation system with PSO based scheduling for PCB remanufacturing plants.
Pavel Vazan, Zuzana Cervenanska, Janette Kotianova & Gabriela Krizanova. (2019) The impact of selected priority rules on production goals. The impact of selected priority rules on production goals.
Dominik Kress, David Müller & Jenny Nossack. (2018) A worker constrained flexible job shop scheduling problem with sequence-dependent setup times. OR Spectrum 41:1, pages 179-217.
Crossref
Yong Zhou, Jian-Jun Yang & Lian-Yu Zheng. (2019) Hyper-Heuristic Coevolution of Machine Assignment and Job Sequencing Rules for Multi-Objective Dynamic Flexible Job Shop Scheduling. IEEE Access 7, pages 68-88.
Crossref
Su Nguyen, Mengjie Zhang, Mark Johnston & Kay Chen Tan. 2019. Evolutionary and Swarm Intelligence Algorithms. Evolutionary and Swarm Intelligence Algorithms 143 167 .
David Müller, Dominik Kress & Jenny Nossack. 2019. Operations Research Proceedings 2018. Operations Research Proceedings 2018 481 488 .
Su Nguyen, Mengjei Zhang, Damminda Alahakoon & Kay Chen Tan. (2018) Visualizing the Evolution of Computer Programs for Genetic Programming [Research Frontier]. IEEE Computational Intelligence Magazine 13:4, pages 77-94.
Crossref
Jiafu Wan, Baotong Chen, Shiyong Wang, Min Xia, Di Li & Chengliang Liu. (2018) Fog Computing for Energy-Aware Load Balancing and Scheduling in Smart Factory. IEEE Transactions on Industrial Informatics 14:10, pages 4548-4556.
Crossref
Su Nguyen, Mengjie Zhang & Kay Chen Tan. (2018) Adaptive charting genetic programming for dynamic flexible job shop scheduling. Adaptive charting genetic programming for dynamic flexible job shop scheduling.
John Park, Yi Mei, Su Nguyen, Gang Chen & Mengjie Zhang. (2018) An investigation of ensemble combination schemes for genetic programming based hyper-heuristic approaches to dynamic job shop scheduling. Applied Soft Computing 63, pages 72-86.
Crossref
Daniel Yska, Yi Mei & Mengjie Zhang. 2018. Genetic Programming. Genetic Programming 306 321 .
Fangfang Zhang, Yi Mei & Mengjie Zhang. 2018. AI 2018: Advances in Artificial Intelligence. AI 2018: Advances in Artificial Intelligence 766 772 .
Fangfang Zhang, Yi Mei & Mengjie Zhang. 2018. AI 2018: Advances in Artificial Intelligence. AI 2018: Advances in Artificial Intelligence 472 484 .
Yi Mei, Su Nguyen, Bing Xue & Mengjie Zhang. (2017) An Efficient Feature Selection Algorithm for Evolving Job Shop Scheduling Rules With Genetic Programming. IEEE Transactions on Emerging Topics in Computational Intelligence 1:5, pages 339-353.
Crossref
Su Nguyen, Mengjie Zhang & Kay Chen Tan. (2017) Surrogate-Assisted Genetic Programming With Simplified Models for Automated Design of Dispatching Rules. IEEE Transactions on Cybernetics 47:9, pages 2951-2965.
Crossref
Su Nguyen & Mengjie Zhang. (2017) A PSO-based hyper-heuristic for evolving dispatching rules in job shop scheduling. A PSO-based hyper-heuristic for evolving dispatching rules in job shop scheduling.
Jorge Orestes Cerdeira, Isabel Cristina Lopes & Eliana Costa e Silva. (2017) Scheduling the Repairment of Aircrafts' Engines. Scheduling the Repairment of Aircrafts' Engines.
Su Nguyen, Yi Mei & Mengjie Zhang. (2017) Genetic programming for production scheduling: a survey with a unified framework. Complex & Intelligent Systems 3:1, pages 41-66.
Crossref
Yi Mei, Su Nguyen & Mengjie Zhang. 2017. Simulated Evolution and Learning. Simulated Evolution and Learning 435 447 .
Yi Mei, Su Nguyen & Mengjie Zhang. 2017. Genetic Programming. Genetic Programming 147 163 .
Ahmed W. El-Bouri. (2016) A score-based dispatching rule for job shop scheduling. A score-based dispatching rule for job shop scheduling.
Chanchal Saha, Faisal Aqlan, Sarah S. Lam & Warren Boldrin. (2016) A decision support system for real-time order management in a heterogeneous production environment. Expert Systems with Applications 60, pages 16-26.
Crossref
Yi Mei, Mengjie Zhang & Su Nyugen. (2016) Feature Selection in Evolving Job Shop Dispatching Rules with Genetic Programming. Feature Selection in Evolving Job Shop Dispatching Rules with Genetic Programming.
Michael Riley, Yi Mei & Mengjie Zhang. (2016) Improving job shop dispatching rules via terminal weighting and adaptive mutation in genetic programming. Improving job shop dispatching rules via terminal weighting and adaptive mutation in genetic programming.
Atiya Masood, Yi Mei, Gang Chen & Mengjie Zhang. (2016) Many-objective genetic programming for job-shop scheduling. Many-objective genetic programming for job-shop scheduling.
Jurgen Branke, Su Nguyen, Christoph W. Pickardt & Mengjie Zhang. (2016) Automated Design of Production Scheduling Heuristics: A Review. IEEE Transactions on Evolutionary Computation 20:1, pages 110-124.
Crossref
Shihui Jia, Jonathan F. Bard, Rodolfo Chacon & John Stuber. (2015) Improving performance of dispatch rules for daily scheduling of assembly and test operations. Computers & Industrial Engineering 90, pages 86-106.
Crossref
Jing Huang & Gürsel A. Süer. (2015) A dispatching rule-based genetic algorithm for multi-objective job shop scheduling using fuzzy satisfaction levels. Computers & Industrial Engineering 86, pages 29-42.
Crossref
Su Nguyen, Mengjie Zhang, Mark Johnston & Kay Chen Tan. (2015) Automatic Programming via Iterated Local Search for Dynamic Job Shop Scheduling. IEEE Transactions on Cybernetics 45:1, pages 1-14.
Crossref
Gabriel Zambrano Rey, Thérèse Bonte, Vittaldas Prabhu & Damien Trentesaux. (2014) Reducing myopic behavior in FMS control: A semi-heterarchical simulation–optimization approach. Simulation Modelling Practice and Theory 46, pages 53-75.
Crossref
Xiaohua Wang & Haibin Duan. (2014) A hybrid biogeography-based optimization algorithm for job shop scheduling problem. Computers & Industrial Engineering 73, pages 96-114.
Crossref
Hui Lu, Xiaoteng Wang & Jing Liu. (2014) Constraint Handling Technique in Test Task Scheduling Problem. Information Technology Journal 13:8, pages 1495-1504.
Crossref
Su Nguyen, Mengjie Zhang, Mark Johnston & Kay Chen Tan. 2013. Automated Scheduling and Planning. Automated Scheduling and Planning 251 282 .

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Order Reprints Request Corporate Permissions

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

Request Academic Permissions

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.

Related research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.