Chuang Wang , Di Fan , Yang Liu , Shan Ren , Jin Wang
{"title":"考虑工人熟练程度差异的双资源柔性作业车间调度","authors":"Chuang Wang , Di Fan , Yang Liu , Shan Ren , Jin Wang","doi":"10.1016/j.cor.2025.107216","DOIUrl":null,"url":null,"abstract":"<div><div>Currently, the increasing attention to resource constraints in production systems is driven by the notable distribution of workers across all age groups within the production shop and the discrepancy of their proficiency in operating machines. It takes time and knowledge to improve workers’ proficiency. And as the workforce retires later, the longer working hours of older workers can help them gain more experience. With the improvement of accumulated experience, the time spent on human-related tasks such as machine debugging, checking, cleaning, and other necessary preparation processes before processing will be significantly reduced. Considering these factors is crucial when making production decisions, necessitating the adaptation of job assignments to suit the capabilities of individual workers. Through this approach, the economic indicators of ‘people-oriented manufacturing’ advocated by Industry 5.0 and workshop production can be jointly realized. In this scenario, a mathematical model is constructed with the objective of minimizing the sum of setup time and processing time for the double-resource flexible job shop scheduling problem (DRCFJSP), considering the differences in worker skill levels and varying process setup times based on this. The model takes the skills and proficiency of workers into consideration as well. Given the problem’s characteristics, the migratory bird optimization algorithm (MBO) is applied to address this issue. Finally, a comparative experiment is carried out on a simulation example. The experimental results verify that incorporating the influence of workers with different proficiency on preparation time into the scheduling model can significantly optimize the total production completion time.</div></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":"184 ","pages":"Article 107216"},"PeriodicalIF":4.3000,"publicationDate":"2025-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Dual-resource flexible job shop scheduling considering worker proficiency differences\",\"authors\":\"Chuang Wang , Di Fan , Yang Liu , Shan Ren , Jin Wang\",\"doi\":\"10.1016/j.cor.2025.107216\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Currently, the increasing attention to resource constraints in production systems is driven by the notable distribution of workers across all age groups within the production shop and the discrepancy of their proficiency in operating machines. It takes time and knowledge to improve workers’ proficiency. And as the workforce retires later, the longer working hours of older workers can help them gain more experience. With the improvement of accumulated experience, the time spent on human-related tasks such as machine debugging, checking, cleaning, and other necessary preparation processes before processing will be significantly reduced. Considering these factors is crucial when making production decisions, necessitating the adaptation of job assignments to suit the capabilities of individual workers. Through this approach, the economic indicators of ‘people-oriented manufacturing’ advocated by Industry 5.0 and workshop production can be jointly realized. In this scenario, a mathematical model is constructed with the objective of minimizing the sum of setup time and processing time for the double-resource flexible job shop scheduling problem (DRCFJSP), considering the differences in worker skill levels and varying process setup times based on this. The model takes the skills and proficiency of workers into consideration as well. Given the problem’s characteristics, the migratory bird optimization algorithm (MBO) is applied to address this issue. Finally, a comparative experiment is carried out on a simulation example. The experimental results verify that incorporating the influence of workers with different proficiency on preparation time into the scheduling model can significantly optimize the total production completion time.</div></div>\",\"PeriodicalId\":10542,\"journal\":{\"name\":\"Computers & Operations Research\",\"volume\":\"184 \",\"pages\":\"Article 107216\"},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2025-07-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers & Operations Research\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0305054825002448\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Operations Research","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0305054825002448","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Currently, the increasing attention to resource constraints in production systems is driven by the notable distribution of workers across all age groups within the production shop and the discrepancy of their proficiency in operating machines. It takes time and knowledge to improve workers’ proficiency. And as the workforce retires later, the longer working hours of older workers can help them gain more experience. With the improvement of accumulated experience, the time spent on human-related tasks such as machine debugging, checking, cleaning, and other necessary preparation processes before processing will be significantly reduced. Considering these factors is crucial when making production decisions, necessitating the adaptation of job assignments to suit the capabilities of individual workers. Through this approach, the economic indicators of ‘people-oriented manufacturing’ advocated by Industry 5.0 and workshop production can be jointly realized. In this scenario, a mathematical model is constructed with the objective of minimizing the sum of setup time and processing time for the double-resource flexible job shop scheduling problem (DRCFJSP), considering the differences in worker skill levels and varying process setup times based on this. The model takes the skills and proficiency of workers into consideration as well. Given the problem’s characteristics, the migratory bird optimization algorithm (MBO) is applied to address this issue. Finally, a comparative experiment is carried out on a simulation example. The experimental results verify that incorporating the influence of workers with different proficiency on preparation time into the scheduling model can significantly optimize the total production completion time.
期刊介绍:
Operations research and computers meet in a large number of scientific fields, many of which are of vital current concern to our troubled society. These include, among others, ecology, transportation, safety, reliability, urban planning, economics, inventory control, investment strategy and logistics (including reverse logistics). Computers & Operations Research provides an international forum for the application of computers and operations research techniques to problems in these and related fields.