{"title":"The hybrid metaheuristic scheduling model for garment manufacturing on-demand","authors":"Мoch Sаiful Umam","doi":"10.31763/sitech.v2i2.504","DOIUrl":null,"url":null,"abstract":"The latest technology milestone drives the fashion industry to implement on-demand production services. This study introduces a decision-making scheme in the manufacturing on-demand production scheduling of the garment industry using a hybrid metaheuristic model to meet consumer demand in the digital economy as quickly as possible. Then we conduct computational experiments based on the real-world case study and compare the hybrid metaheuristic method with existing approaches. The experimental results demonstrate that the hybrid metaheuristic approach can yield very efficient solutions to the scheduling problem; it can save production completion time by 22.6%; it shows promising performance compared to the existing methods.","PeriodicalId":123344,"journal":{"name":"Science in Information Technology Letters","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science in Information Technology Letters","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31763/sitech.v2i2.504","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The latest technology milestone drives the fashion industry to implement on-demand production services. This study introduces a decision-making scheme in the manufacturing on-demand production scheduling of the garment industry using a hybrid metaheuristic model to meet consumer demand in the digital economy as quickly as possible. Then we conduct computational experiments based on the real-world case study and compare the hybrid metaheuristic method with existing approaches. The experimental results demonstrate that the hybrid metaheuristic approach can yield very efficient solutions to the scheduling problem; it can save production completion time by 22.6%; it shows promising performance compared to the existing methods.