{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,10]],"date-time":"2026-02-10T20:42:10Z","timestamp":1770756130971,"version":"3.50.0"},"reference-count":61,"publisher":"PeerJ","license":[{"start":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T00:00:00Z","timestamp":1765152000000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia","award":["PNURSP2025R239"],"award-info":[{"award-number":["PNURSP2025R239"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:p>Poultry manufacturing plants employing Dynamic Flexible Job Shop Scheduling Problems (DFJSSP) face workflow disruptions due to unexpected machine failures. Efficient rescheduling algorithms are essential to reallocate operations and minimize disruptions. This study proposes two machine failure handling strategies utilizing Grey Wolf Optimization (GWO) and Particle Swarm Optimization (PSO) techniques. Initially, the proposed algorithms generate a healthy state schedule that is executed and monitored in the manufacturing plant. In the event of a machine failure, the digital model of the system triggers a rescheduling process. In the first scenario, the finished operations are excluded out of the schedule, and the remaining operations are optimally rescheduled, excluding faulty machines. The results showed that GWO emphasizes aggressive makespan reduction but at higher energy costs, while PSO provides a more balanced trade-off with slightly longer makespan but lower energy consumption. In the second scenario, an operation-shifting technique is applied; disrupted operations are rescheduled on alternative machines, while following operations retain their initial assignments but are delayed. Both scenarios incorporate operational constraints and evaluate energy consumption to ensure efficiency. Accordingly, an energy consumption analysis report is provided to the decision makers to select the best scenario. The algorithm is implemented and tested under varying failure conditions. Both scenarios, with the proposed optimization algorithms, demonstrate effective rescheduling, with energy consumption analysis confirming rational energy use. As a confirmative step, the proposed GWO and PSO algorithms have been applied to the standard Brandimarte benchmark test cases with different problem sizes. The results proved the validity of the algorithms. Then, the system\u2019s performance has been investigated under different disruption times and failure scenarios. The proposed rescheduling algorithm proves robust and superior in handling machine failures. It minimizes workflow disruptions, ensures operational feasibility, and optimizes energy consumption, making it a reliable solution for poultry manufacturing plants. Finally, to validate the efficiency and effectiveness of the proposed algorithm, we compare the outcomes of the two scenarios by applying them to the same problem and analyzing the behavior of each rescheduling strategy. Two powerful optimization techniques, GWO and PSO, were employed to assess the robustness of the rescheduling plan. Both techniques produced very similar results, demonstrating the consistency and reliability of the proposed approach.<\/jats:p>","DOI":"10.7717\/peerj-cs.3379","type":"journal-article","created":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T08:24:26Z","timestamp":1765182266000},"page":"e3379","source":"Crossref","is-referenced-by-count":1,"title":["Swarm algorithms for sustainable dynamic flexible job shop rescheduling under machine breakdown in smart manufacturing plants"],"prefix":"10.7717","volume":"11","author":[{"given":"Nehal","family":"Tarek","sequence":"first","affiliation":[{"name":"Department of Information Systems, Faculty of Computers and Information, Menoufia University, Shibin El Kom, Al Minufiyah, Egypt"},{"name":"Faculty of Computers and Artificial Intelligence, Menoufia National University, Tukh Tambisha, Al Minufiyah, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Samia Allaoua","family":"Chelloug","sequence":"additional","affiliation":[{"name":"Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Soha","family":"Alhelaly","sequence":"additional","affiliation":[{"name":"College of Computing and Informatics, Saudi Electronic University, Riyadh, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Nancy A.","family":"El-Hefnawy","sequence":"additional","affiliation":[{"name":"Information Systems Department, Faculty of Computers and Informatics, Tanta University, Tanta, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hatem","family":"Abdel-Kader","sequence":"additional","affiliation":[{"name":"Department of Information Systems, Faculty of Computers and Information, Menoufia University, Shibin El Kom, Al Minufiyah, Egypt"},{"name":"Faculty of Computers and Artificial Intelligence, Menoufia National University, Tukh Tambisha, Al Minufiyah, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amira","family":"Abdelatey","sequence":"additional","affiliation":[{"name":"Department of Information Systems, Faculty of Computers and Information, Menoufia University, Shibin El Kom, Al Minufiyah, Egypt"},{"name":"Faculty of Computers and Artificial Intelligence, Menoufia National University, Tukh Tambisha, Al Minufiyah, Egypt"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"4443","published-online":{"date-parts":[[2025,12,8]]},"reference":[{"issue":"4","key":"10.7717\/peerj-cs.3379\/ref-1","doi-asserted-by":"publisher","first-page":"871","DOI":"10.5267\/j.ijiec.2024.7.004","article-title":"Energy-efficient scheduling for a flexible job shop problem considering rework processes and new job arrival","volume":"15","author":"Albayrak","year":"2024","journal-title":"International Journal of Industrial Engineering Computations"},{"key":"10.7717\/peerj-cs.3379\/ref-2","doi-asserted-by":"publisher","first-page":"425","DOI":"10.1016\/j.jmsy.2020.06.005","article-title":"Greedy randomized adaptive search for dynamic flexible job-shop scheduling","volume":"56","author":"Baykaso\u011flu","year":"2020","journal-title":"Journal of Manufacturing Systems"},{"issue":"3","key":"10.7717\/peerj-cs.3379\/ref-3","doi-asserted-by":"publisher","first-page":"157","DOI":"10.1007\/bf02023073","article-title":"Routing and scheduling in a flexible job shop by tabu search","volume":"41","author":"Brandimarte","year":"1993","journal-title":"Annals of Operations Research"},{"issue":"8","key":"10.7717\/peerj-cs.3379\/ref-4","doi-asserted-by":"publisher","first-page":"1973","DOI":"10.1007\/s10845-015-1084-y","article-title":"Optimisation of distributed manufacturing flexible job shop scheduling by using hybrid genetic algorithms","volume":"28","author":"Chang","year":"2017","journal-title":"Journal of Intelligent Manufacturing"},{"issue":"2","key":"10.7717\/peerj-cs.3379\/ref-5","doi-asserted-by":"publisher","first-page":"82","DOI":"10.3390\/info15020082","article-title":"Scheduling for the flexible job-shop problem with a dynamic number of machines using deep reinforcement learning","volume":"15","author":"Chang","year":"2024","journal-title":"Information"},{"key":"10.7717\/peerj-cs.3379\/ref-6","doi-asserted-by":"publisher","first-page":"35018","DOI":"10.1109\/ACCESS.2020.2974245","article-title":"Multiobjective evolutionary scheduling and rescheduling of integrated aircraft routing and crew pairing problems","volume":"8","author":"Chen","year":"2020","journal-title":"IEEE Access"},{"key":"10.7717\/peerj-cs.3379\/ref-7","doi-asserted-by":"publisher","first-page":"33486","DOI":"10.1109\/ACCESS.2024.3372396","article-title":"Flexible job shop scheduling method for optimizing mold resource setup time","volume":"12","author":"Cheng","year":"2024","journal-title":"IEEE Access"},{"issue":"2","key":"10.7717\/peerj-cs.3379\/ref-8","doi-asserted-by":"publisher","first-page":"409","DOI":"10.1016\/j.ejor.2023.05.017","article-title":"The flexible job shop scheduling problem: a review","volume":"314","author":"Dauz\u00e8re-P\u00e9r\u00e8s","year":"2024","journal-title":"European Journal of Operational Research"},{"issue":"12","key":"10.7717\/peerj-cs.3379\/ref-9","doi-asserted-by":"publisher","first-page":"6425","DOI":"10.1109\/TII.2019.2938572","article-title":"Digital-twin-based job shop scheduling toward smart manufacturing","volume":"15","author":"Fang","year":"2019","journal-title":"IEEE Transactions on Industrial Informatics"},{"issue":"3","key":"10.7717\/peerj-cs.3379\/ref-10","doi-asserted-by":"publisher","first-page":"1140","DOI":"10.1016\/j.ejor.2022.09.006","article-title":"A hybrid particle swarm optimization and simulated annealing algorithm for the job shop scheduling problem with transport resources","volume":"306","author":"Fontes","year":"2023","journal-title":"European Journal of Operational Research"},{"issue":"1","key":"10.7717\/peerj-cs.3379\/ref-11","doi-asserted-by":"publisher","first-page":"86","DOI":"10.1080\/00207543.2024.2356628","article-title":"Scheduling stochastic distributed flexible job shops using an multi-objective evolutionary algorithm with simulation evaluation","volume":"63","author":"Fu","year":"2024","journal-title":"International Journal of Production Research"},{"issue":"4","key":"10.7717\/peerj-cs.3379\/ref-12","doi-asserted-by":"publisher","first-page":"142","DOI":"10.3390\/a17040142","article-title":"Dynamic events in the flexible job-shop scheduling problem: rescheduling with a hybrid metaheuristic algorithm","volume":"17","author":"Fuladi","year":"2024","journal-title":"Algorithms"},{"key":"10.7717\/peerj-cs.3379\/ref-13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.knosys.2016.06.014","article-title":"Artificial bee colony algorithm for scheduling and rescheduling fuzzy flexible job shop problem with new job insertion","volume":"109","author":"Gao","year":"2016","journal-title":"Knowledge-Based Systems"},{"key":"10.7717\/peerj-cs.3379\/ref-14","doi-asserted-by":"publisher","first-page":"86915","DOI":"10.1109\/ACCESS.2020.2992478","article-title":"Improved Jaya algorithm for flexible job shop rescheduling problem","volume":"8","author":"Gao","year":"2020","journal-title":"IEEE Access"},{"key":"10.7717\/peerj-cs.3379\/ref-15","first-page":"1577","article-title":"Solving job-shop scheduling problems by genetic algorithm","volume":"2","author":"Gen","year":"1994"},{"key":"10.7717\/peerj-cs.3379\/ref-16","article-title":"Dynamic integrated flexible job shop scheduling with transportation robot","author":"He","year":"2021"},{"issue":"9","key":"10.7717\/peerj-cs.3379\/ref-17","doi-asserted-by":"publisher","first-page":"17407","DOI":"10.3934\/mbe.2023774","article-title":"An improved genetic algorithm with dynamic neighborhood search for job shop scheduling problem","volume":"20","author":"Hu","year":"2023","journal-title":"Mathematical Biosciences and Engineering"},{"key":"10.7717\/peerj-cs.3379\/ref-18","article-title":"Industrial machines dataset for electrical load disaggregation","author":"IEEE","year":"2020"},{"key":"10.7717\/peerj-cs.3379\/ref-19","doi-asserted-by":"publisher","first-page":"26231","DOI":"10.1109\/ACCESS.2018.2833552","article-title":"Application of grey wolf optimization for solving combinatorial problems: job shop and flexible job shop scheduling cases","volume":"6","author":"Jiang","year":"2018","journal-title":"IEEE Access"},{"key":"10.7717\/peerj-cs.3379\/ref-20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2018\/8574892","article-title":"Energy-efficient scheduling for a job shop using grey wolf optimization algorithm with double-searching mode","volume":"2018","author":"Jiang","year":"2018","journal-title":"Mathematical Problems in Engineering"},{"issue":"6","key":"10.7717\/peerj-cs.3379\/ref-21","doi-asserted-by":"publisher","first-page":"2586","DOI":"10.3390\/app14062586","article-title":"Research on flexible job shop scheduling problem with handling and setup time based on improved discrete particle swarm algorithm","volume":"14","author":"Kong","year":"2024","journal-title":"Applied Sciences"},{"issue":"11","key":"10.7717\/peerj-cs.3379\/ref-22","doi-asserted-by":"publisher","first-page":"1100","DOI":"10.3390\/machines10111100","article-title":"Solving the flexible job shop scheduling problem using a discrete improved grey wolf optimization algorithm","volume":"10","author":"Kong","year":"2022","journal-title":"Machines"},{"key":"10.7717\/peerj-cs.3379\/ref-23","doi-asserted-by":"publisher","first-page":"102443","DOI":"10.1016\/j.rcim.2022.102443","article-title":"Digital twin-based job shop anomaly detection and dynamic scheduling","volume":"79","author":"Li","year":"2023","journal-title":"Robotics and Computer-Integrated Manufacturing"},{"issue":"9","key":"10.7717\/peerj-cs.3379\/ref-24","doi-asserted-by":"publisher","first-page":"2105","DOI":"10.1007\/s11431-022-2096-6","article-title":"Improved gray wolf optimizer for distributed flexible job shop scheduling problem","volume":"65","author":"Li","year":"2022","journal-title":"Science China Technological Sciences"},{"issue":"1","key":"10.7717\/peerj-cs.3379\/ref-25","doi-asserted-by":"publisher","first-page":"18124","DOI":"10.1038\/s41598-025-01255-0","article-title":"Application of Levy flight-based harmony search algorithm for the flexible job shop scheduling","volume":"15","author":"Li","year":"2025","journal-title":"Scientific Reports"},{"key":"10.7717\/peerj-cs.3379\/ref-26","doi-asserted-by":"publisher","first-page":"54596","DOI":"10.1109\/ACCESS.2023.3281364","article-title":"Multi-strategy dynamic evolution-based improved MOEA\/D algorithm for solving multi-objective fuzzy flexible job shop scheduling problem","volume":"11","author":"Liu","year":"2023","journal-title":"IEEE Access"},{"key":"10.7717\/peerj-cs.3379\/ref-27","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1016\/j.engappai.2016.10.013","article-title":"A hybrid multi-objective grey wolf optimizer for dynamic scheduling in a real-world welding industry","volume":"57","author":"Lu","year":"2017","journal-title":"Engineering Applications of Artificial Intelligence"},{"key":"10.7717\/peerj-cs.3379\/ref-28","doi-asserted-by":"publisher","first-page":"728","DOI":"10.1016\/j.asoc.2018.11.043","article-title":"A multi-objective cellular grey wolf optimizer for hybrid flowshop scheduling problem considering noise pollution","volume":"75","author":"Lu","year":"2019","journal-title":"Applied Soft Computing"},{"key":"10.7717\/peerj-cs.3379\/ref-29","doi-asserted-by":"publisher","first-page":"113721","DOI":"10.1016\/j.eswa.2020.113721","article-title":"An efficient memetic algorithm for distributed flexible job shop scheduling problem with transfers","volume":"160","author":"Luo","year":"2020","journal-title":"Expert Systems with Applications"},{"issue":"16","key":"10.7717\/peerj-cs.3379\/ref-30","doi-asserted-by":"publisher","first-page":"4973","DOI":"10.1080\/00207543.2021.1946193","article-title":"Distributed job-shop rescheduling problem considering reconfigurability of machines: a self-adaptive hybrid equilibrium optimiser","volume":"60","author":"Mahmoodjanloo","year":"2021","journal-title":"International Journal of Production Research"},{"issue":"6","key":"10.7717\/peerj-cs.3379\/ref-31","doi-asserted-by":"publisher","first-page":"583","DOI":"10.1007\/s10951-010-0222-9","article-title":"A survey of problems, solution techniques, and future challenges in scheduling semiconductor manufacturing operations","volume":"14","author":"M\u00f6nch","year":"2011","journal-title":"Journal of Scheduling"},{"issue":"23","key":"10.7717\/peerj-cs.3379\/ref-32","doi-asserted-by":"publisher","first-page":"13016","DOI":"10.3390\/su132313016","article-title":"A Q-learning rescheduling approach to the flexible job shop problem combining energy and productivity objectives","volume":"13","author":"Naimi","year":"2021","journal-title":"Sustainability"},{"issue":"2\u20133","key":"10.7717\/peerj-cs.3379\/ref-33","doi-asserted-by":"publisher","first-page":"559","DOI":"10.1007\/s10845-025-02585-6","article-title":"Reinforcement learning in dynamic job shop scheduling: a comprehensive review of AI-driven approaches in modern manufacturing","volume":"33","author":"Ngwu","year":"2025","journal-title":"Journal of Intelligent Manufacturing"},{"key":"10.7717\/peerj-cs.3379\/ref-34","doi-asserted-by":"publisher","first-page":"3585","DOI":"10.1109\/access.2018.2793265","article-title":"Digital twin and big data towards smart manufacturing and industry 4.0: 360 degree comparison","volume":"6","author":"Qi","year":"2018","journal-title":"IEEE Access"},{"issue":"3","key":"10.7717\/peerj-cs.3379\/ref-35","doi-asserted-by":"publisher","first-page":"567","DOI":"10.1016\/j.ifacol.2015.06.141","article-title":"About the importance of autonomy and digital twins for the future of manufacturing","volume":"48","author":"Rosen","year":"2015","journal-title":"IFAC-PapersOnLine"},{"issue":"4","key":"10.7717\/peerj-cs.3379\/ref-36","doi-asserted-by":"publisher","first-page":"791","DOI":"10.1016\/j.cie.2006.09.002","article-title":"A hybrid particle swarm optimization for job shop scheduling problem","volume":"51","author":"Sha","year":"2006","journal-title":"Computers & Industrial Engineering"},{"issue":"298","key":"10.7717\/peerj-cs.3379\/ref-37","doi-asserted-by":"publisher","first-page":"198","DOI":"10.1016\/j.ins.2014.11.036","article-title":"Mathematical modeling and multi-objective evolutionary algorithms applied to dynamic flexible job shop scheduling problems","volume":"2015","author":"Shen","year":"2015","journal-title":"Information Sciences"},{"issue":"4","key":"10.7717\/peerj-cs.3379\/ref-38","doi-asserted-by":"publisher","first-page":"1921","DOI":"10.3390\/app11041921","article-title":"Job shop scheduling problem optimization by means of graph-based algorithm","volume":"11","author":"Stastny","year":"2021","journal-title":"Applied Sciences"},{"key":"10.7717\/peerj-cs.3379\/ref-39","first-page":"65","article-title":"Solving job shop scheduling problem using genetic algorithm with penalty function","volume":"1","author":"Sun","year":"2010","journal-title":"International Journal of Intelligent Information Processing"},{"issue":"5","key":"10.7717\/peerj-cs.3379\/ref-40","doi-asserted-by":"publisher","first-page":"1008","DOI":"10.1109\/TFUZZ.2019.2895562","article-title":"A hybrid cooperative coevolution algorithm for fuzzy flexible job shop scheduling","volume":"27","author":"Sun","year":"2019","journal-title":"IEEE Transactions on Fuzzy Systems"},{"issue":"3","key":"10.7717\/peerj-cs.3379\/ref-41","doi-asserted-by":"publisher","first-page":"119359","DOI":"10.1016\/j.eswa.2022.119359","article-title":"Hybrid genetic algorithm with variable neighborhood search for flexible job shop scheduling problem in a machining system","volume":"215","author":"Sun","year":"2023","journal-title":"Expert Systems with Applications"},{"issue":"1","key":"10.7717\/peerj-cs.3379\/ref-42","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1016\/j.ejor.2021.03.069","article-title":"Multiobjective optimization for complex flexible job-shop scheduling problems","volume":"296","author":"Tamssaouet","year":"2022","journal-title":"European Journal of Operational Research"},{"key":"10.7717\/peerj-cs.3379\/ref-43","doi-asserted-by":"publisher","first-page":"107557","DOI":"10.1016\/j.cie.2021.107557","article-title":"A fatigue-conscious dual resource constrained flexible job shop scheduling problem by enhanced NSGA-II: an application from casting workshop","volume":"160","author":"Tan","year":"2021","journal-title":"Computers & Industrial Engineering"},{"key":"10.7717\/peerj-cs.3379\/ref-44","doi-asserted-by":"publisher","first-page":"19863","DOI":"10.1109\/ACCESS.2025.3532600","article-title":"Knowledge graph-enhanced digital twin framework for optimized job shop scheduling in smart manufacturing","volume":"13","author":"Tarek","year":"2025","journal-title":"IEEE Access"},{"key":"10.7717\/peerj-cs.3379\/ref-45","doi-asserted-by":"publisher","first-page":"2073","DOI":"10.16182\/j.issn1004731x.joss.20-0732","article-title":"Optimal scheduling and decision-making method for dynamic flexible job shop","volume":"32","author":"Wang","year":"2020","journal-title":"Journal of System Simulation"},{"issue":"12","key":"10.7717\/peerj-cs.3379\/ref-46","doi-asserted-by":"publisher","first-page":"8519","DOI":"10.1109\/tii.2022.3165636","article-title":"Solving multiobjective fuzzy job-shop scheduling problem by a hybrid adaptive differential evolution algorithm","volume":"18","author":"Wang","year":"2022","journal-title":"IEEE Transactions on Industrial Informatics"},{"issue":"4","key":"10.7717\/peerj-cs.3379\/ref-47","doi-asserted-by":"publisher","first-page":"1246","DOI":"10.3390\/pr13041246","article-title":"Dynamic scheduling for multi-objective flexible job shops with machine breakdown by deep reinforcement learning","volume":"13","author":"Wu","year":"2025","journal-title":"Processes"},{"issue":"3","key":"10.7717\/peerj-cs.3379\/ref-48","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1049\/iet-cim.2018.0009","article-title":"Review on flexible job shop scheduling","volume":"1","author":"Xie","year":"2019","journal-title":"IET Collaborative Intelligent Manufacturing"},{"issue":"1","key":"10.7717\/peerj-cs.3379\/ref-49","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1016\/j.ijpe.2012.04.015","article-title":"Robust scheduling for multi-objective flexible job-shop problems with random machine breakdowns","volume":"141","author":"Xiong","year":"2013","journal-title":"International Journal of Production Economics"},{"key":"10.7717\/peerj-cs.3379\/ref-50","doi-asserted-by":"publisher","first-page":"19990","DOI":"10.1109\/access.2018.2890566","article-title":"A digital-twin-assisted fault diagnosis using deep transfer learning","volume":"7","author":"Xu","year":"2019","journal-title":"IEEE Access"},{"issue":"3","key":"10.7717\/peerj-cs.3379\/ref-51","doi-asserted-by":"publisher","first-page":"101836","DOI":"10.1016\/j.swevo.2024.101836","article-title":"Quantum particle swarm optimization with chaotic encoding schemes for flexible job-shop scheduling problem","volume":"93","author":"Xu","year":"2025","journal-title":"Swarm and Evolutionary Computation"},{"issue":"2","key":"10.7717\/peerj-cs.3379\/ref-52","doi-asserted-by":"publisher","first-page":"103","DOI":"10.3390\/systems11020103","article-title":"Energy-saving scheduling for flexible job shop problem with AGV transportation considering emergencies","volume":"11","author":"Zhang","year":"2023","journal-title":"Systems"},{"key":"10.7717\/peerj-cs.3379\/ref-53","doi-asserted-by":"publisher","first-page":"146","DOI":"10.1016\/j.jmsy.2020.04.008","article-title":"Digital twin enhanced dynamic job-shop scheduling","volume":"58","author":"Zhang","year":"2021","journal-title":"Journal of Manufacturing Systems"},{"key":"10.7717\/peerj-cs.3379\/ref-54","doi-asserted-by":"publisher","first-page":"1136","DOI":"10.1177\/0020294020946352","article-title":"Dynamic flexible job shop scheduling method based on improved gene expression programming","volume":"54","author":"Zhang","year":"2022","journal-title":"Measurement and Control"},{"issue":"22","key":"10.7717\/peerj-cs.3379\/ref-55","doi-asserted-by":"publisher","first-page":"10304","DOI":"10.3390\/app142210304","article-title":"A two-individual-based evolutionary algorithm for flexible assembly job shop scheduling problem with uncertain interval processing times","volume":"14","author":"Zheng","year":"2024","journal-title":"Applied Sciences"},{"key":"10.7717\/peerj-cs.3379\/ref-56","doi-asserted-by":"publisher","first-page":"226042\u2013226058","DOI":"10.1109\/ACCESS.2020.3043880","article-title":"Performance assessment of dynamic flexible assembly job shop control methods","volume":"8","author":"Zhong","year":"2020","journal-title":"IEEE Access"},{"issue":"1","key":"10.7717\/peerj-cs.3379\/ref-57","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1007\/s11063-024-11488-1","article-title":"Research on solving flexible job shop scheduling problem based on improved GWO algorithm SS-GWO","volume":"56","author":"Zhou","year":"2024","journal-title":"Neural Processing Letters"},{"key":"10.7717\/peerj-cs.3379\/ref-58","doi-asserted-by":"publisher","first-page":"125113\u2013125121","DOI":"10.1109\/ACCESS.2019.2938548","article-title":"An adaptive real-time scheduling method for flexible job shop scheduling problem with combined processing constraint","volume":"7","author":"Zhu","year":"2019","journal-title":"IEEE Access"},{"key":"10.7717\/peerj-cs.3379\/ref-59","doi-asserted-by":"publisher","first-page":"121205","DOI":"10.1016\/j.eswa.2023.121205","article-title":"An effective reformative memetic algorithm for distributed flexible job-shop scheduling problem with order cancellation","volume":"237","author":"Zhu","year":"2024","journal-title":"Expert Systems with Applications"},{"issue":"4","key":"10.7717\/peerj-cs.3379\/ref-60","doi-asserted-by":"publisher","first-page":"119840","DOI":"10.1016\/j.eswa.2023.119840","article-title":"Dynamic distributed flexible job-shop scheduling problem considering operation inspection","volume":"224","author":"Zhu","year":"2023","journal-title":"Expert Systems with Applications"},{"key":"10.7717\/peerj-cs.3379\/ref-61","doi-asserted-by":"publisher","first-page":"109235","DOI":"10.1016\/j.asoc.2022.109235","article-title":"A shuffled cellular evolutionary grey wolf optimizer for flexible job shop scheduling problem with tree-structure job precedence constraints","volume":"125","author":"Zhu","year":"2022","journal-title":"Applied Soft Computing"}],"container-title":["PeerJ Computer Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/peerj.com\/articles\/cs-3379.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/peerj.com\/articles\/cs-3379.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/peerj.com\/articles\/cs-3379.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/peerj.com\/articles\/cs-3379.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T08:24:32Z","timestamp":1765182272000},"score":1,"resource":{"primary":{"URL":"https:\/\/peerj.com\/articles\/cs-3379"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,8]]},"references-count":61,"alternative-id":["10.7717\/peerj-cs.3379"],"URL":"https:\/\/doi.org\/10.7717\/peerj-cs.3379","archive":["CLOCKSS","LOCKSS","Portico"],"relation":{},"ISSN":["2376-5992"],"issn-type":[{"value":"2376-5992","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,8]]},"article-number":"e3379"}}