{"title":"Order Acceptance and Capacity Allocation Policies Based on Revenue Management","authors":"Lifan Fan, Xu Chen","doi":"10.1109/ICIII.2008.98","DOIUrl":null,"url":null,"abstract":"Selective order acceptance and capacity allocation policies are vital to the success of make-to-order (MTO) manufactures. The importance of these two policies has been acknowledged both in manufacturing industry and academic research. After the huge success of revenue management in retail and service industries, there are more and more MTO manufactures introducing revenue management techniques into MTO manufacturing industry. In this paper, we consider the application of revenue management into a make-to-order system. Based on the maximizing revenue policy, we use the stochastic dynamic programming to model the MTO revenue problem, and solve it with the certainty equivalence approach, then the optimal order acceptance and capacity allocation polices are proposed-accept a new coming order as long as its revenue is greater than or equal to the minimum of the shadow revenue, and if it is accepted, allocate it a machine which with the minimum shadow revenue. In the end, the further research directions are presented.","PeriodicalId":185591,"journal":{"name":"2008 International Conference on Information Management, Innovation Management and Industrial Engineering","volume":"70 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 International Conference on Information Management, Innovation Management and Industrial Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIII.2008.98","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Selective order acceptance and capacity allocation policies are vital to the success of make-to-order (MTO) manufactures. The importance of these two policies has been acknowledged both in manufacturing industry and academic research. After the huge success of revenue management in retail and service industries, there are more and more MTO manufactures introducing revenue management techniques into MTO manufacturing industry. In this paper, we consider the application of revenue management into a make-to-order system. Based on the maximizing revenue policy, we use the stochastic dynamic programming to model the MTO revenue problem, and solve it with the certainty equivalence approach, then the optimal order acceptance and capacity allocation polices are proposed-accept a new coming order as long as its revenue is greater than or equal to the minimum of the shadow revenue, and if it is accepted, allocate it a machine which with the minimum shadow revenue. In the end, the further research directions are presented.