{"title":"使用增强型遗传编程超启发式优化具有机器故障和作业到达不确定性的混合流水车间的三目标批量流水排程","authors":"","doi":"10.1016/j.cor.2024.106817","DOIUrl":null,"url":null,"abstract":"<div><p>Lot-streaming scheduling has been widely recognized as a means to improve shop productivity, but there is few research on lot-streaming scheduling problems under dynamic disturbances. To fill the gap, lot-streaming scheduling optimization approach for hybrid flow shops with uncertainties in machine breakdowns and job arrivals is proposed. A mathematical model is formulated with objectives of minimizing maximum tardiness, total idle energy consumption of the machine, and maximum makespan. Since the Genetic Programming Hyper Heuristic algorithm has better results in solving dynamic scheduling problems, a Collaborative Harmony Search-based Genetic Programming Hyper Heuristic (CHS-GPHH) is presented to solve the dynamic lot-streaming hybrid flow shop scheduling problem (DLS-HFSSP) with the two dynamic events occurring simultaneously. In the improved algorithm, a neighborhood structure based on harmony search is developed for lot splitting. To verify the effectiveness of the proposed approach, the various comparative studies c are conducted on the lot-streaming dynamic hybrid flow shop scheduling. The results demonstrate the effectiveness of each improvement component of the CHS-GPHH, and verify that CHS-GPHH is an effective approach to deal with DLS-HFSSP with the in all the scenarios.</p></div>","PeriodicalId":10542,"journal":{"name":"Computers & Operations Research","volume":null,"pages":null},"PeriodicalIF":4.1000,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Tri-objective lot-streaming scheduling optimization for hybrid flow shops with uncertainties in machine breakdowns and job arrivals using an enhanced genetic programming hyper-heuristic\",\"authors\":\"\",\"doi\":\"10.1016/j.cor.2024.106817\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Lot-streaming scheduling has been widely recognized as a means to improve shop productivity, but there is few research on lot-streaming scheduling problems under dynamic disturbances. To fill the gap, lot-streaming scheduling optimization approach for hybrid flow shops with uncertainties in machine breakdowns and job arrivals is proposed. A mathematical model is formulated with objectives of minimizing maximum tardiness, total idle energy consumption of the machine, and maximum makespan. Since the Genetic Programming Hyper Heuristic algorithm has better results in solving dynamic scheduling problems, a Collaborative Harmony Search-based Genetic Programming Hyper Heuristic (CHS-GPHH) is presented to solve the dynamic lot-streaming hybrid flow shop scheduling problem (DLS-HFSSP) with the two dynamic events occurring simultaneously. In the improved algorithm, a neighborhood structure based on harmony search is developed for lot splitting. To verify the effectiveness of the proposed approach, the various comparative studies c are conducted on the lot-streaming dynamic hybrid flow shop scheduling. The results demonstrate the effectiveness of each improvement component of the CHS-GPHH, and verify that CHS-GPHH is an effective approach to deal with DLS-HFSSP with the in all the scenarios.</p></div>\",\"PeriodicalId\":10542,\"journal\":{\"name\":\"Computers & Operations Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.1000,\"publicationDate\":\"2024-08-23\",\"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/S0305054824002892\",\"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/S0305054824002892","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}
Tri-objective lot-streaming scheduling optimization for hybrid flow shops with uncertainties in machine breakdowns and job arrivals using an enhanced genetic programming hyper-heuristic
Lot-streaming scheduling has been widely recognized as a means to improve shop productivity, but there is few research on lot-streaming scheduling problems under dynamic disturbances. To fill the gap, lot-streaming scheduling optimization approach for hybrid flow shops with uncertainties in machine breakdowns and job arrivals is proposed. A mathematical model is formulated with objectives of minimizing maximum tardiness, total idle energy consumption of the machine, and maximum makespan. Since the Genetic Programming Hyper Heuristic algorithm has better results in solving dynamic scheduling problems, a Collaborative Harmony Search-based Genetic Programming Hyper Heuristic (CHS-GPHH) is presented to solve the dynamic lot-streaming hybrid flow shop scheduling problem (DLS-HFSSP) with the two dynamic events occurring simultaneously. In the improved algorithm, a neighborhood structure based on harmony search is developed for lot splitting. To verify the effectiveness of the proposed approach, the various comparative studies c are conducted on the lot-streaming dynamic hybrid flow shop scheduling. The results demonstrate the effectiveness of each improvement component of the CHS-GPHH, and verify that CHS-GPHH is an effective approach to deal with DLS-HFSSP with the in all the scenarios.
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.