{"title":"Efficient robust design of public rescue service system","authors":"J. Janáček, Marek Kvet","doi":"10.1109/SOLI.2017.8120962","DOIUrl":null,"url":null,"abstract":"Public rescue service system design is determined by deployment of limited number of service centers at positions from a given set of possible locations. The robust service system design is usually performed so that the design complies with specified scenarios by minimizing the maximal value of the objective functions corresponding to the particular scenarios. As the set of detrimental scenarios is not evaluated by probabilities of their occurrence, a question of robustness measurement arises. Within this paper, we suggest so called “price of robustness” to appraise deterioration of the standard objective function as a consequence of robustness improvement and we also introduce “gain of robustness” to asset the robustness improvement. Furthermore, we suggest a method for robust system design, which optimizes robust efficiency of the resulting solution.","PeriodicalId":190544,"journal":{"name":"2017 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SOLI.2017.8120962","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
Public rescue service system design is determined by deployment of limited number of service centers at positions from a given set of possible locations. The robust service system design is usually performed so that the design complies with specified scenarios by minimizing the maximal value of the objective functions corresponding to the particular scenarios. As the set of detrimental scenarios is not evaluated by probabilities of their occurrence, a question of robustness measurement arises. Within this paper, we suggest so called “price of robustness” to appraise deterioration of the standard objective function as a consequence of robustness improvement and we also introduce “gain of robustness” to asset the robustness improvement. Furthermore, we suggest a method for robust system design, which optimizes robust efficiency of the resulting solution.