{"title":"Warehousing Cost Optimization in the Restaurant Brands International (Canada) Inc.","authors":"Chao Yang, Yuan Wang","doi":"10.62051/bsn66s98","DOIUrl":null,"url":null,"abstract":"Restaurant Brands International (RBI), a global catering company, faces significant warehousing cost challenges, primarily driven by labor expenses. This study aims to minimize these costs while maintaining service quality through an integer linear programming model for optimal employee scheduling. The model incorporates various constraints, such as the minimum number of shifts per week and employee preferences, and considers real data from RBI’s financial reports. Sensitivity analyses were conducted to assess the impact of salary adjustments, changes in the minimum number of shifts, and the reduction of part-time work opportunities. The results indicate that the optimized scheduling model can significantly reduce labor costs and improve operational efficiency. The findings provide a reference for RBI and other companies with similar warehousing needs, emphasizing the importance of flexible scheduling, employee satisfaction, and adapting to peak demand periods.","PeriodicalId":515906,"journal":{"name":"Transactions on Economics, Business and Management Research","volume":"30 18","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Transactions on Economics, Business and Management Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.62051/bsn66s98","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
Restaurant Brands International (RBI), a global catering company, faces significant warehousing cost challenges, primarily driven by labor expenses. This study aims to minimize these costs while maintaining service quality through an integer linear programming model for optimal employee scheduling. The model incorporates various constraints, such as the minimum number of shifts per week and employee preferences, and considers real data from RBI’s financial reports. Sensitivity analyses were conducted to assess the impact of salary adjustments, changes in the minimum number of shifts, and the reduction of part-time work opportunities. The results indicate that the optimized scheduling model can significantly reduce labor costs and improve operational efficiency. The findings provide a reference for RBI and other companies with similar warehousing needs, emphasizing the importance of flexible scheduling, employee satisfaction, and adapting to peak demand periods.