{"title":"Optimal Control of Service Systems with Heterogeneous Servers and Priority Customers","authors":"David Chen, Ruoran Chen, Rowan Wang, Xuan Wang","doi":"10.2139/ssrn.3628440","DOIUrl":null,"url":null,"abstract":"We study non-preemptive queueing systems consisting multiple classes of customers with different waiting cost rates and multiple servers with heterogeneous service rates. We compare two common-in-practice systems (dedicated system and work-conserving flexible priority system) and characterize conditions for each one to be more favorable. Under the objective of minimizing discounted total waiting cost, we develop a Markov decision process formulation and analytically characterize the structure of the optimal dynamic server assignment policy. We prove that, the optimal policy is of a threshold type with intentional idleness. We also invent an approach to compute the optimal threshold values. Through numerical experiments, we quantify the advantage of the optimal policy.","PeriodicalId":275253,"journal":{"name":"Operations Research eJournal","volume":"194 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Operations Research eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3628440","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
We study non-preemptive queueing systems consisting multiple classes of customers with different waiting cost rates and multiple servers with heterogeneous service rates. We compare two common-in-practice systems (dedicated system and work-conserving flexible priority system) and characterize conditions for each one to be more favorable. Under the objective of minimizing discounted total waiting cost, we develop a Markov decision process formulation and analytically characterize the structure of the optimal dynamic server assignment policy. We prove that, the optimal policy is of a threshold type with intentional idleness. We also invent an approach to compute the optimal threshold values. Through numerical experiments, we quantify the advantage of the optimal policy.