{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T23:20:53Z","timestamp":1784244053223,"version":"3.55.0"},"reference-count":41,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2024,3,28]],"date-time":"2024-03-28T00:00:00Z","timestamp":1711584000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"the Basic Science Research Program through the National Research Foundation of Korea (NRF), funded by the Ministry of Education","award":["2021R1I1A3052605"],"award-info":[{"award-number":["2021R1I1A3052605"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>In the real world of manufacturing systems, production planning is crucial for organizing and optimizing various manufacturing process components. The objective of this paper is to present a methodology for both static scheduling and dynamic scheduling. In the proposed method, a hybrid algorithm is utilized to optimize the static flexible job-shop scheduling problem (FJSP) and dynamic flexible job-shop scheduling problem (DFJSP). This algorithm integrates the genetic algorithm (GA) as a global optimization technique with a simulated annealing (SA) algorithm serving as a local search optimization approach to accelerate convergence and prevent getting stuck in local minima. Additionally, variable neighborhood search (VNS) is utilized for efficient neighborhood search within this hybrid algorithm framework. For the FJSP, the proposed hybrid algorithm is simulated on a 40-benchmark dataset to evaluate its performance. Comparisons among the proposed hybrid algorithm and other algorithms are provided to show the effectiveness of the proposed algorithm, ensuring that the proposed hybrid algorithm can efficiently solve the FJSP, with 38 out of 40 instances demonstrating better results. The primary objective of this study is to perform dynamic scheduling on two datasets, including both single-purpose machine and multi-purpose machine datasets, using the proposed hybrid algorithm with a rescheduling strategy. By observing the results of the DFJSP, dynamic events such as a single machine breakdown, a single job arrival, multiple machine breakdowns, and multiple job arrivals demonstrate that the proposed hybrid algorithm with the rescheduling strategy achieves significant improvement and the proposed method obtains the best new solution, resulting in a significant decrease in makespan.<\/jats:p>","DOI":"10.3390\/a17040142","type":"journal-article","created":{"date-parts":[[2024,3,28]],"date-time":"2024-03-28T12:22:46Z","timestamp":1711628566000},"page":"142","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":36,"title":["Dynamic Events in the Flexible Job-Shop Scheduling Problem: Rescheduling with a Hybrid Metaheuristic Algorithm"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-4430-5699","authenticated-orcid":false,"given":"Shubhendu Kshitij","family":"Fuladi","sequence":"first","affiliation":[{"name":"Department of Information Systems, Pukyong National University, Busan 608737, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2168-7983","authenticated-orcid":false,"given":"Chang-Soo","family":"Kim","sequence":"additional","affiliation":[{"name":"Department of Information Systems, Pukyong National University, Busan 608737, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,3,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"9270802","DOI":"10.1155\/2018\/9270802","article-title":"Recent Research Trends in Genetic Algorithm Based Flexible Job Shop Scheduling Problems","volume":"2018","author":"Amjad","year":"2018","journal-title":"Math. Probl. Eng."},{"key":"ref_2","doi-asserted-by":"crossref","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":"298","author":"Shen","year":"2015","journal-title":"Inf. Sci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1287\/moor.1.2.117","article-title":"The Complexity of Flowshop and Jobshop Scheduling. Your Use of the JSTOR Archive Indicat","volume":"1","author":"Garey","year":"1976","journal-title":"Math. Oper. Res."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.promfg.2019.02.006","article-title":"A Review of Dynamic Job Shop Scheduling Techniques","volume":"30","author":"Mohan","year":"2019","journal-title":"Procedia Manuf."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1016\/j.ijpe.2011.04.020","article-title":"Robust and Stable Flexible Job Shop Scheduling with Random Machine Breakdowns Using a Hybrid Genetic Algorithm","volume":"132","author":"Elmekkawy","year":"2011","journal-title":"Int. J. Prod. Econ."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Wang, Z., Zhang, J., and Si, J. (2020). Dynamic Job Shop Scheduling Problem with New Job Arrivals: A Survey, Springer.","DOI":"10.1007\/978-981-32-9050-1_75"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"360","DOI":"10.1016\/j.cie.2016.06.018","article-title":"A Stable Reactive Approach in Dynamic Flexible Flow Shop Scheduling with Unexpected Disruptions: A Case Study","volume":"98","author":"Rahmani","year":"2016","journal-title":"Comput. Ind. Eng."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"6363","DOI":"10.1080\/00207543.2018.1468095","article-title":"Solving Multi-Objective Rescheduling Problems in Dynamic Permutation Flow Shop Environments with Disruptions","volume":"56","author":"Valledor","year":"2018","journal-title":"Int. J. Prod. Res."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"3563","DOI":"10.1016\/j.eswa.2010.08.145","article-title":"An Effective Genetic Algorithm for the Flexible Job-Shop Scheduling Problem","volume":"38","author":"Zhang","year":"2011","journal-title":"Expert Syst. Appl."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"480","DOI":"10.1016\/j.procs.2020.02.061","article-title":"Improved Genetic Algorithm for Solving Flexible Job Shop Scheduling Problem","volume":"166","author":"Luo","year":"2020","journal-title":"Procedia Comput. Sci."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1527858","DOI":"10.1155\/2017\/1527858","article-title":"A Variable Interval Rescheduling Strategy for Dynamic Flexible Job Shop Scheduling Problem by Improved Genetic Algorithm","volume":"2017","author":"Wang","year":"2017","journal-title":"J. Adv. Transp."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1016\/j.ejor.2009.01.008","article-title":"An Improved Genetic Algorithm for the Distributed and Flexible Job-Shop Scheduling Problem","volume":"200","author":"Pezzella","year":"2010","journal-title":"Eur. J. Oper. Res."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1635","DOI":"10.1080\/0305215X.2022.2106477","article-title":"Simulated-Annealing-Based Hyper-Heuristic for Flexible Job-Shop Scheduling","volume":"55","author":"Lim","year":"2022","journal-title":"Eng. Optim."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"563","DOI":"10.1007\/s00170-005-0375-4","article-title":"Flexible Job Shop Scheduling with Tabu Search Algorithms","volume":"32","author":"Fattahi","year":"2007","journal-title":"Int. J. Adv. Manuf. Technol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"186474","DOI":"10.1109\/ACCESS.2020.3029868","article-title":"Research on Adaptive Job Shop Scheduling Problems Based on Dueling Double DQN","volume":"8","author":"Han","year":"2020","journal-title":"IEEE Access"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1016\/j.ijpe.2016.01.016","article-title":"An Effective Hybrid Genetic Algorithm and Tabu Search for Flexible Job Shop Scheduling Problem","volume":"174","author":"Li","year":"2016","journal-title":"Int. J. Prod. Econ."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Escamilla-Serna, N.J., Seck-Tuoh-Mora, J.C., Medina-Marin, J., Barragan-Vite, I., and Corona-Armenta, J.R. (2022). A Hybrid Search Using Genetic Algorithms and Random-Restart Hill-Climbing for Flexible Job Shop Scheduling Instances with High Flexibility. Appl. Sci., 12.","DOI":"10.3390\/app12168050"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"3678","DOI":"10.1016\/j.proeng.2011.08.689","article-title":"A Hybrid Algorithm for Flexible Job-Shop Scheduling Problem","volume":"15","author":"Tang","year":"2011","journal-title":"Procedia Eng."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"3516","DOI":"10.1080\/00207543.2012.751509","article-title":"A Hybrid Genetic Algorithm and Tabu Search for a Multi-Objective Dynamic Job Shop Scheduling Problem","volume":"51","author":"Zhang","year":"2013","journal-title":"Int. J. Prod. Res."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"3020","DOI":"10.1080\/00207543.2018.1524165","article-title":"A Heuristic Model for Dynamic Flexible Job Shop Scheduling Problem Considering Variable Processing Times","volume":"57","author":"Katebi","year":"2019","journal-title":"Int. J. Prod. Res."},{"key":"ref_21","doi-asserted-by":"crossref","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":"2021","journal-title":"Meas. Control"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1016\/j.cirpj.2009.10.001","article-title":"Dynamic Scheduling in Flexible Job Shop Systems by Considering Simultaneously Efficiency and Stability","volume":"2","author":"Fattahi","year":"2010","journal-title":"CIRP J. Manuf. Sci. Technol."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.cie.2016.03.011","article-title":"Hybrid Genetic Algorithms for Minimizing Makespan in Dynamic Job Shop Scheduling Problem","volume":"96","author":"Kundakci","year":"2016","journal-title":"Comput. Ind. Eng."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Wei, H., Li, S., Jiang, H., Hu, J., and Hu, J. (2018). Hybrid Genetic Simulated Annealing Algorithm for Improved Flow Shop Scheduling with Makespan Criterion. Appl. Sci., 8.","DOI":"10.3390\/app8122621"},{"key":"ref_25","first-page":"100","article-title":"Hybrid Genetic Algorithms with Simulating Annealing for University Course Timetabling Problems Publication of Little Lion Scientific R & D, Islamabad Pakistan","volume":"29","year":"2011","journal-title":"J. Theor. Appl. Inf. Technol."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1016\/j.procir.2021.11.069","article-title":"Evolving Dispatching Rules Using Genetic Programming for Multi-Objective Dynamic Job Shop Scheduling with Machine Breakdowns","volume":"104","author":"Shady","year":"2021","journal-title":"Procedia CIRP"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Pocol, C.B., Stanca, L., Dabija, D.C., C\u00e2mpian, V., Mi\u0219coiu, S., and Pop, I.D. (2023). A QCA Analysis of Knowledge Co-Creation Based on University\u2013Industry Relationships. Mathematics, 11.","DOI":"10.3390\/math11020388"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"106855","DOI":"10.1016\/j.chb.2021.106855","article-title":"What Makes an AI Device Human-like? The Role of Interaction Quality, Empathy and Perceived Psychological Anthropomorphic Characteristics in the Acceptance of Artificial Intelligence in the Service Industry","volume":"122","author":"Pelau","year":"2021","journal-title":"Comput. Human Behav."},{"key":"ref_29","first-page":"1","article-title":"Preventive Maintenance for the Flexible Flowshop Scheduling under Uncertainty: A Waste-to-Energy System","volume":"28","author":"Gholizadeh","year":"2021","journal-title":"Environ. Sci. Pollut. Res."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"102770","DOI":"10.1016\/j.omega.2022.102770","article-title":"Scheduling of Multi-Robot Job Shop Systems in Dynamic Environments: Mixed-Integer Linear Programming and Constraint Programming Approaches","volume":"115","author":"Foumani","year":"2023","journal-title":"Omega"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1002\/tqem.21538","article-title":"A Review of Textile Industry: Wet Processing, Environmental Impacts, and Effluent Treatment Methods","volume":"27","author":"Madhav","year":"2018","journal-title":"Environ. Qual. Manag."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1007\/s00170-021-07444-1","article-title":"Modeling of Textile Manufacturing Processes Using Intelligent Techniques: A Review","volume":"116","author":"He","year":"2021","journal-title":"Int. J. Adv. Manuf. Technol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1007\/BF01719451","article-title":"Tabu Search for the Job-Shop Scheduling Problem with Multi-Purpose Machines","volume":"15","author":"Hurink","year":"1994","journal-title":"OR Spektrum"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"2068","DOI":"10.1038\/s41598-024-51778-1","article-title":"GAILS: An Effective Multi-Object Job Shop Scheduler Based on Genetic Algorithm and Iterative Local Search","volume":"14","author":"Shao","year":"2024","journal-title":"Sci. Rep."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"816","DOI":"10.1016\/j.ejor.2019.01.047","article-title":"Variable Neighborhood Search for the Set Orienteering Problem and Its Application to Other Orienteering Problem Variants","volume":"276","author":"Faigl","year":"2019","journal-title":"Eur. J. Oper. Res."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"4429","DOI":"10.1109\/TCYB.2020.3026651","article-title":"A Modified Genetic Algorithm with New Encoding and Decoding Methods for Integrated Process Planning and Scheduling Problem","volume":"51","author":"Liu","year":"2021","journal-title":"IEEE Trans. Cybern."},{"key":"ref_37","first-page":"100233","article-title":"Sustainable Distributed Permutation Flow-Shop Scheduling Model Based on a Triple Bottom Line Concept","volume":"24","author":"Woodward","year":"2021","journal-title":"J. Ind. Inf. Integr."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1016\/S0377-2217(97)00420-7","article-title":"Some New Results on Simulated Annealing Applied to the Job Shop Scheduling Problem","volume":"113","author":"Kolonko","year":"1999","journal-title":"Eur. J. Oper. Res."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"101507","DOI":"10.1016\/j.swevo.2024.101507","article-title":"A Customized Adaptive Large Neighborhood Search Algorithm for Solving a Multi-Objective Home Health Care Problem in a Pandemic Environment","volume":"86","author":"Liu","year":"2024","journal-title":"Swarm Evol. Comput."},{"key":"ref_40","unstructured":"Lawrence, S. (1984). Resouce Constrained Project Scheduling: An Experimental Investigation of Heuristic Scheduling Techniques (Supplement), Graduate School of Industrial Administration, Carnegie-Mellon University."},{"key":"ref_41","first-page":"94","article-title":"Flexible Job Shop Dynamic Scheduling Problem Research with Machine Fault","volume":"31","author":"Wu","year":"2015","journal-title":"Mach. Des. Res."}],"container-title":["Algorithms"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-4893\/17\/4\/142\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T14:20:27Z","timestamp":1760106027000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-4893\/17\/4\/142"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,28]]},"references-count":41,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2024,4]]}},"alternative-id":["a17040142"],"URL":"https:\/\/doi.org\/10.3390\/a17040142","relation":{},"ISSN":["1999-4893"],"issn-type":[{"value":"1999-4893","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,3,28]]}}}