Relevant bibliographies by topics / Dynamic flexible job shop

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Dynamic flexible job shop'

Author: Grafiati
Published: 2 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Dynamic flexible job shop"

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Zhang, Liping, Xinyu Li, Long Wen, and Guohui Zhang. "An Efficient Memetic Algorithm for Dynamic Flexible Job Shop Scheduling with Random Job Arrivals." International Journal of Software Science and Computational Intelligence 5, no. 1 (2013): 63–77. http://dx.doi.org/10.4018/ijssci.2013010105.

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Much of the research on flexible job shop scheduling problem has ignored dynamic events in dynamic environment where there are complex constraints and a variety of unexpected disruptions. This paper proposes an efficient memetic algorithm to solve the flexible job shop scheduling problem with random job arrivals. Firstly, a periodic policy is presented to update the problem condition and generate the rescheduling point. Secondly, the efficient memetic algorithm with a new local search procedure is proposed to optimize the problem at each rescheduling point. Five kinds of neighborhood structure
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Pan, Ying, Dong Juan Xue, Tian Yi Gao, Li Bin Zhou, and Xiao Yu Xie. "Modeling and Scheme Generation of Dynamic Flexible Job-Shop Scheduling." Applied Mechanics and Materials 423-426 (September 2013): 2232–36. http://dx.doi.org/10.4028/www.scientific.net/amm.423-426.2232.

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Aiming at uncertain information and dynamic characteristic during flexible job-shop scheduling process, some kind of dynamic scheduling method for flexible job-shop scheduling problem (FJSP) is put forward based on real-time adjustment. A dynamic simulation solution mode framework is presented for FJSP. This framework is inspired by adaptive control, combined with the robust scheduling and foreseeing scheduling. It has both advantages of such two scheduling methods, and its stable and highly efficient. Preliminary scheme generation method based on foreseeing dynamics scheduling is introduced t
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Long, Xiaojun, Jingtao Zhang, Kai Zhou, and Tianguo Jin. "Dynamic Self-Learning Artificial Bee Colony Optimization Algorithm for Flexible Job-Shop Scheduling Problem with Job Insertion." Processes 10, no. 3 (2022): 571. http://dx.doi.org/10.3390/pr10030571.

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To solve the problem of inserting new job into flexible job-shops, this paper proposes a dynamic self-learning artificial bee colony (DSLABC) optimization algorithm to solve dynamic flexible job-shop scheduling problem (DFJSP). Through the reasonable arrangement of the processing sequence of the jobs and the corresponding relationship between the operations and the machines, the makespan can be shortened, the economic benefit of the job-shop and the utilization rate of the processing machine can be improved. Firstly, the Q-learning algorithm and the traditional artificial bee colony (ABC) algo
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Wang, Chun, Jiapeng Chen, Binzi Xu, and Sheng Liu. "A Discrete Improved Gray Wolf Optimization Algorithm for Dynamic Distributed Flexible Job Shop Scheduling Considering Random Job Arrivals and Machine Breakdowns." Processes 13, no. 7 (2025): 1987. https://doi.org/10.3390/pr13071987.

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Dueto uncertainties in real-world production, dynamic factors have become increasingly critical in the research of distributed flexible job shop scheduling problems. Effectively responding to dynamic events can significantly enhance the adaptability and quality of scheduling solutions, thereby improving the resilience of manufacturing systems. This study addresses the dynamic distributed flexible job shop scheduling problem, which involves random job arrivals and machine breakdowns, and proposes an effective discrete improved gray wolf optimization (DIGWO) algorithm-based predictive–reactive m
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Li, Juan, Xianghong Tian, and Jing Liu. "Dynamic Data Scheduling of a Flexible Industrial Job Shop Based on Digital Twin Technology." Discrete Dynamics in Nature and Society 2022 (August 3, 2022): 1–10. http://dx.doi.org/10.1155/2022/1009507.

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Aiming at the problems of premature convergence of existing workshop dynamic data scheduling methods and the decline in product output, a flexible industrial job shop dynamic data scheduling method based on digital twin technology is proposed. First, digital twin technology is proposed, which provides a design and theoretical basis for the simulation tour of a flexible industrial job shop, building the all-factor digital information fusion model of a flexible industrial workshop to comprehensively control the all-factor digital information of the workshops. A CGA algorithm is proposed by intro
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Wang, Yajun, Junyu Leng, Xiaoqi Liu, Jiajia Wang, and Qiunan Meng. "A Method for Dynamic Insertion Order Scheduling in Flexible Job Shops Based on Digital Twins." Applied Sciences 12, no. 23 (2022): 12430. http://dx.doi.org/10.3390/app122312430.

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Various production disturbances occurring in the flexible job shop production process may affect the production of the workshop, some of which may lead to the prolongation of production completion time. Therefore, a flexible job shop dynamic scheduling method based on digital twins is proposed and a dynamic scheduling framework is constructed. Compared with the traditional workshop, the digital twin-based flexible job shop can upload the relevant production data of the physical workshop to the data management center in real time, and after fusion processing the data can work cooperatively with
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Wang, Yanjiao, and Jieru Han. "A FJSSP Method Based on Dynamic Multi-Objective Squirrel Search Algorithm." International Journal of Antennas and Propagation 2021 (October 15, 2021): 1–19. http://dx.doi.org/10.1155/2021/6062689.

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This paper comprehensively analyzes the characteristics of flexible job shop scheduling problem (FJSSP), takes the dynamic factors in the actual scheduling process such as the arrival and departure of jobs, the breakdown and recovery of machines into account at the same time, and establishes a new dynamic multi-objective mathematical model. Take the Squirrel Search Algorithm (SSA) as the core evolution strategy, and combine the multi-objective framework and the dynamic processing technology to solve the established mathematical model. Experimental results show that the mathematical model propo
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M., Sanatizadeh M.A. Badamchizadeh S. Khanmohammadi D. Ashtiani Haghighi. "A New Method for Solving Dynamic Flexible Job Shop Scheduling Problems Integrating Genetic Algorithm and Priority Rules." International Journal of Engineering Works 1, no. 2 (2014): 26–31. https://doi.org/10.5281/zenodo.15746.

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Dynamic flexible job shop scheduling problems has been one of the important and strongly NP-hard problem of manufacturing systems for many years. Most of the proposed algorithms are based on priority rules; By using these rules, the arrived jobs go to a long queue of waited jobs and sometimes it takes a long time for a job to be processed. In this paper a new approach, integrating of priority rules and genetic algorithm is presented, by decomposition of a dynamic problem to smaller dynamic and static problems. A module converts the queue of dynamic jobs to static, and then a genetic algorithm
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Pan, Ying, Dong Juan Xue, Tian Yi Gao, Li Bin Zhou, and Xiao Yu Xie. "Research on Strategy of Dynamic Flexible Job-Shop Scheduling." Applied Mechanics and Materials 423-426 (September 2013): 2237–43. http://dx.doi.org/10.4028/www.scientific.net/amm.423-426.2237.

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A dynamic scheduling method for FJSP is put forward based on real-time adjustment of controllable margin, aiming at uncertain information and dynamic characteristic during practical job-shop scheduling process. Strategy and methods of dynamic scheduling adjustment are presented, which respond to real-time event. In view of practical operation condition and accuracy demands, two methods are proposed. One is rescheduling that condenses domain, the other is scheduling updating based on adjustment. Such strategy obtains dynamic robust scheduling of FJSP to ensure the real-time of algorithm, contin
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Xu, Xiang Min, and Xi Fan Yao. "Application of Ontology in Event-Driven Job-Shop Scheduling Problems." Applied Mechanics and Materials 775 (July 2015): 458–63. http://dx.doi.org/10.4028/www.scientific.net/amm.775.458.

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Aiming at the flexible flow-shop scheduling problem of cloud manufacturing, this paper introduces event driven concept and apply ontologies to Job-Shop scheduling problem FT46. The inference of ontology models allows the system to gain the dynamic information of workshop, and then rule engine is used to match event patterns to optimize the job shop scheduling problem.
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Dissertations / Theses on the topic "Dynamic flexible job shop"

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Luscombe, Ruth. "A dynamic real time scheduling methodology for the emergency department." Thesis, Queensland University of Technology, 2015. https://eprints.qut.edu.au/86505/1/Ruth_Luscombe_Thesis.pdf.

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This project constructs a scheduling solution for the Emergency Department. The schedules are generated in real-time to adapt to new patient arrivals and changing conditions. An integrated scheduling formulation assigns patients to beds and treatment tasks to resources. The schedule efficiency is assessed using waiting time and total care time experienced by patients. The solution algorithm incorporates dispatch rules, meta-heuristics and a new extended disjunctive graph formulation which provide high quality solutions in a fast time-frame for real time decision support. This algorithm can
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Struijker, Boudier Ivar. "Job shop scheduling with flexible maintenance planning." Thesis, Lancaster University, 2017. http://eprints.lancs.ac.uk/87305/.

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This thesis considers the scheduling challenges encountered at a particular facility in the nuclear industry. The scheduling problem is modelled as a variant of the job shop scheduling problem. Important aspects of the considered problem include the scheduling of jobs with both soft and hard due dates, and the integration of maintenance planning with job scheduling. Two variants of the scheduling problem are considered: The first variant makes the classic job shop assumption of infinite queueing capacity at each machine, while such queueing capacity is non-existent in the second variant. Witho
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Balci, Serife Aytug. "Solution Approaches For Flexible Job Shop Scheduling Problems." Master's thesis, METU, 2013. http://etd.lib.metu.edu.tr/upload/12615676/index.pdf.

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discrete parts manufacturing industries. We are motivated by the production environment of Roketsan Missiles Industries Incorporation, operating at Turkish defense industry. Our objective is to minimize the total weighted completion times of the jobs in the system. We formulate the problem as a mixed integer linear program and find that our model could find optimal solutions only to small sized problem instances. For medium and large sized problem instances, we develop heuristic algorithms with high quality approximate solutions in reasonable solution time. Our proposed heuristic algorithm has
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Vilcot, Geoffrey. "Algorithmes approchés pour des problèmes d'ordonnancement multicritères de type job shop flexible et job shop multiressource." Phd thesis, Université François Rabelais - Tours, 2007. http://tel.archives-ouvertes.fr/tel-00198068.

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Ce travail de thèse s'inscrit dans le cadre d'une collaboration industrielle avec la société Volume Software pour le développement du module d'ordonnancement du logiciel "DirectPlanning". Dans ce travail, nous étudions le problème de job shop flexible multicritère et le problème de job shop multiressource multicritère. Notre objectif est de déterminer une approximation du front de Pareto. Nous avons proposé des algorithmes de résolution approchés et plus particulièrement des algorithmes de recherche Tabou et des algorithmes génétiques. Nous avons proposé différentes versions de nos méthodes po
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Wu, Zuobao. "Multi-agent workload control and flexible job shop scheduling." [Tampa, Fla.] : University of South Florida, 2005. http://purl.fcla.edu/fcla/etd/SFE0001193.

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Sousa, Sandra Isabel Ferreira de. "Heuristic approaches for a flexible job-shop scheduling problem." Master's thesis, Universidade de Aveiro, 2016. http://hdl.handle.net/10773/17578.

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Mestrado em Engenharia e Gestão Industrial<br>Este trabalho aborda um novo tipo de problema de escalonamento que pode ser encontrado em várias aplicações do mundo-real, principalmente na indústria transformadora. Em relação à configuração do shop floor, o problema pode ser classificado como flexible job-shop, onde os trabalhos podem ter diferentes rotas ao longo dos recursos e as suas operações têm um conjunto de recursos onde podem ser realizadas. Outras características de processamento abordadas são: datas possíveis de início, restrições de precedência (entre operações de um mesmo trabalho o
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Al-Hinai, Nasr. "OPTIMIZING THE FLEXIBLE JOB-SHOP SCHEDULING PROBLEM USING HYBRIDIZED GENETIC ALGORITHMS." Flexible Services and Manufacturing Journal, 2011. http://hdl.handle.net/1993/4955.

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Flexible job-shop scheduling problem (FJSP) is a generalization of the classical job-shop scheduling problem (JSP). It takes shape when alternative production routing is allowed in the classical job-shop. However, production scheduling becomes very complex as the number of jobs, operations, parts and machines increases. Until recently, scheduling problems were studied assuming that all of the problem parameters are known beforehand. However, such assumption does not reflect the reality as accidents and unforeseen incidents happen in real manufacturing systems. Thus, an optimal schedule that is
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Tejada, Muñoz Guillermo. "Enrutamiento y secuenciación óptimos en un flexible Job Shop multiobjetivo mediante algoritmos genéticos." Doctoral thesis, Universidad Nacional Mayor de San Marcos, 2017. https://hdl.handle.net/20.500.12672/6657.

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Propone una solución óptima al problema de programar (Scheduling) el procesamiento de un conjunto de Jobs (Tareas) en un conjunto de máquinas de una manufactura tipo Flexible Job Shop (FJS-Taller Flexible). La solución minimiza tres criterios: El Maximum Workload (WM), el Total Workload (WT) y el Makespan (CM), es decir, el problema es de Optimización Multiobjetivo. El problema FJS es actualmente estudiado por muchos investigadores porque corresponde a uno de optimización combinatoria muy difícil de resolver (NP-Hard) y porque una solución óptima redunda en una producción eficiente de la manuf
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Wein, Lawrence M., and Jihong Ou. "The Impact of Processing Time Knowledge on Dynamic Job-Shop Scheduling." Massachusetts Institute of Technology, Operations Research Center, 1989. http://hdl.handle.net/1721.1/5388.

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The goal of this paper is to determine if the results for dynamic job-shop scheduling problems are affected by the assumptions made with regard to the processing time distributions and the scheduler's knowledge of the processing times. Three dynamic jobshop scheduling problems (including a two station version of Conway et al.'s [2] nine station symmetric shop) are tested under seven different scenarios, one deterministic and six stochastic, using computer simulation. The deterministic scenario, where the processing times are exponential and observed by the scheduler, has been considered in man
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Previero, Wellington Donizeti. "Estratégias de resolução para o problema de job-shop flexível." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/45/45134/tde-20102016-123243/.

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Nesta tese apresentamos duas estratégias para resolver o problema de job-shop flexível com o objetivo de minimizar o makespan. A primeira estratégia utiliza um algoritmo branch and cut (B&C) e a segunda abordagens matheuristics. O algoritmo B&C utiliza novas classes de inequações válidas, originalmente formulada para o problema de job-shop e estendida para o problema em questão. Para que as inequações válidas sejam eficientes, o modelo proposto por Birgin et al, (2014) (A milp model for an extended version of the fexible job shop problem. Optimization Letters, Springer, v. 8, n. 4, 1417-1431),
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Books on the topic "Dynamic flexible job shop"

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Bär, Schirin. Generic Multi-Agent Reinforcement Learning Approach for Flexible Job-Shop Scheduling. Springer Fachmedien Wiesbaden, 2022. http://dx.doi.org/10.1007/978-3-658-39179-9.

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Berg, L. Gene. Simulation based analysis of flexible manufacturing cells in job-shop environments. University of Wisconsin, 1985.

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Wenzelburger, Philipp. Model Predictive Control Framework for Flexible Job Shop Scheduling. Logos Verlag Berlin, 2022.

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Bär, Schirin. Generic Multi-Agent Reinforcement Learning Approach for Flexible Job-Shop Scheduling. Springer Fachmedien Wiesbaden GmbH, 2022.

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Book chapters on the topic "Dynamic flexible job shop"

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Zhang, Fangfang, Yi Mei, and Mengjie Zhang. "Surrogate-Assisted Genetic Programming for Dynamic Flexible Job Shop Scheduling." In AI 2018: Advances in Artificial Intelligence. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03991-2_69.

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Ferreira, Inês C., Bernardo Firme, Miguel S. E. Martins, et al. "Artificial Bee Colony Algorithm Applied to Dynamic Flexible Job Shop Problems." In Information Processing and Management of Uncertainty in Knowledge-Based Systems. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-50146-4_19.

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Han, Wenmin, Zhuoya Feng, and Jiahui Cai. "Dynamic Scheduling Study of Flexible Job Shop Considering Machine Failure Rate." In Advances in Social Science, Education and Humanities Research. Atlantis Press SARL, 2023. http://dx.doi.org/10.2991/978-2-38476-126-5_6.

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Zhang, Fangfang, Su Nguyen, Yi Mei, and Mengjie Zhang. "Learning Scheduling Heuristics for Multi-objective Dynamic Flexible Job Shop Scheduling." In Genetic Programming for Production Scheduling. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-4859-5_12.

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Zhang, Fangfang, Yi Mei, and Mengjie Zhang. "Genetic Programming with Multi-tree Representation for Dynamic Flexible Job Shop Scheduling." In AI 2018: Advances in Artificial Intelligence. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03991-2_43.

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Hou, Zhenyu, Lixiang Zhang, Yiheng Wang, and Yaoguang Hu. "Deep Reinforcement Learning for Dynamic Flexible Job-Shop Scheduling with Automated Guided Vehicles." In Lecture Notes in Mechanical Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-0194-0_11.

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Yska, Daniel, Yi Mei, and Mengjie Zhang. "Genetic Programming Hyper-Heuristic with Cooperative Coevolution for Dynamic Flexible Job Shop Scheduling." In Lecture Notes in Computer Science. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-77553-1_19.

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Guo, Chen, and Wenyong Luo. "Interval Type-2 Fuzzy Flexible Job-Shop Dynamic Scheduling Considering Variable Remaining Processing Capacity." In Lecture Notes in Electrical Engineering. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-6937-7_69.

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Nie, Li, Yuewei Bai, Xiaogang Wang, and Kai Liu. "Discover Scheduling Strategies with Gene Expression Programming for Dynamic Flexible Job Shop Scheduling Problem." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-31020-1_45.

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Zhang, Fangfang, Yi Mei, Su Nguyen, and Mengjie Zhang. "Guided Subtree Selection for Genetic Operators in Genetic Programming for Dynamic Flexible Job Shop Scheduling." In Lecture Notes in Computer Science. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44094-7_17.

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Conference papers on the topic "Dynamic flexible job shop"

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Destouet, Candice, Houda Tlahig, Belgacem Bettayeb, and Bélahcène Mazari. "Dynamic and Sustainable Flexible Job Shop Scheduling Problem under Worker Unavailability Risk." In 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE). IEEE, 2024. http://dx.doi.org/10.1109/case59546.2024.10711610.

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Johnson, Dazzle, Gang Chen, and Yuqian Lu. "Multi-Agent Scheduler for the Continuous Dynamic Flexible Job Shop Scheduling Problem." In 2024 IEEE 20th International Conference on Automation Science and Engineering (CASE). IEEE, 2024. http://dx.doi.org/10.1109/case59546.2024.10711538.

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Feng, Zeyu, Xu Liang, and Zhiyuan Zou. "Hierarchical Crossover-Based NSGA-III for Dynamic Flexible Job Shop Scheduling Problem." In 2024 7th International Conference on Algorithms, Computing and Artificial Intelligence (ACAI). IEEE, 2024. https://doi.org/10.1109/acai63924.2024.10899739.

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Qiao, Zhuoyin, Fangfang Zhang, Yi Mei, and Mengjie Zhang. "Preference-Based Multi-Objective Genetic Programming for Energy-Efficient Dynamic Flexible Job Shop Scheduling." In 2025 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2025. https://doi.org/10.1109/cec65147.2025.11043041.

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Chen, Jiayin, Ya-Hui Jia, Ying Bi, and Wei-Neng Chen. "Generate a Single Heuristic for Multiple Dynamic Flexible Job Shop Scheduling Tasks by Genetic Programming." In 2024 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2024. http://dx.doi.org/10.1109/cec60901.2024.10611762.

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Zhu, Luyao, Fangfang Zhang, Mengyuan Feng, Ke Chen, Xiaodong Zhu, and Mengjie Zhang. "Crossover Operators Between Multiple Scheduling Heuristics with Genetic Programming for Dynamic Flexible Job Shop Scheduling." In 2024 IEEE Congress on Evolutionary Computation (CEC). IEEE, 2024. http://dx.doi.org/10.1109/cec60901.2024.10612212.

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Chen, Le, Dunbing Tang, Zhen Zhao, and Liping Wang. "Probing a novel dual-phase adaptive deep learning approach for dynamic flexible job shop scheduling." In Third International Conference on Intelligent Mechanical and Human-Computer Interaction Technology (IHCIT 2024), edited by Xiangjie Kong and Xingjian Wang. SPIE, 2024. http://dx.doi.org/10.1117/12.3049738.

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Xu, Kai, Binzi Xu, Dengchao Huang, and Chun Wang. "A Rule and Network Dual-Driven Dynamic Scheduling Approach for Complex Flexible Manufacturing Job Shop." In 2024 7th International Conference on Robotics, Control and Automation Engineering (RCAE). IEEE, 2024. https://doi.org/10.1109/rcae62637.2024.10834207.

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Li, Xinyan, and Shuangyun Xing. "Dynamic scheduling problem of multi-objective dual resource flexible job shop based on improved genetic algorithm." In 2024 43rd Chinese Control Conference (CCC). IEEE, 2024. http://dx.doi.org/10.23919/ccc63176.2024.10662528.

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Zhang, Qi, and Bin Zhang. "Research on dynamic flexible job shop scheduling problem based on discrete particle swarm optimization with readjustment strategy." In 10th International Conference on Mechanical Engineering, Materials, and Automation Technology (MMEAT 2024), edited by Yunhui Liu and Zili Li. SPIE, 2024. http://dx.doi.org/10.1117/12.3046596.

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Reports on the topic "Dynamic flexible job shop"

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Guliashki, Vassil, and Leoneed Kirilov. Algorithm Generating Initial Population of Schedules for Population-based Algorithms Solving Flexible Job Shop Problems. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, 2019. http://dx.doi.org/10.7546/crabs.2019.06.01.

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