{"title":"具有椭球不确定性集的不确定lcp间隙函数公式$$\\Gamma $$ -鲁棒对应物解的存在性","authors":"Lulin Tan, Wei Hong Yang, Jinbiao Pan","doi":"10.1007/s10898-023-01340-6","DOIUrl":null,"url":null,"abstract":"<p>In this paper, we give some existence theorems of solutions to <span>\\(\\Gamma \\)</span>-robust counterparts of gap function formulations of uncertain linear complementarity problems, in which <span>\\(\\Gamma \\)</span> plays a role in adjusting the robustness of the model against the level of conservatism of solutions. If the <span>\\(\\Gamma \\)</span>-robust uncertainty set is nonconvex, it is hard to prove the existence of solutions to the corresponding robust counterpart. Using techniques of asymptotic functions, we establish existence theorems of solutions to the corresponding robust counterpart. For the case of nonconvex <span>\\(\\Gamma \\)</span>-robust ellipsoidal uncertainty sets, these existence results are not proved in the paper [Krebs et al., Int. Trans. Oper. Res. 29 (2022), pp. 417–441]; for the case of convex <span>\\(\\Gamma \\)</span>-robust ellipsoidal uncertainty sets, our existence theorems are obtained under the conditions which are much weaker than those in Krebs’ paper. Finally, a case study for the uncertain traffic equilibrium problem is considered to illustrate the effects of nonconvex uncertainty sets on the level of conservatism of robust solutions.\n</p>","PeriodicalId":15961,"journal":{"name":"Journal of Global Optimization","volume":"55 2","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2023-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Existence of solutions to $$\\\\Gamma $$ -robust counterparts of gap function formulations of uncertain LCPs with ellipsoidal uncertainty sets\",\"authors\":\"Lulin Tan, Wei Hong Yang, Jinbiao Pan\",\"doi\":\"10.1007/s10898-023-01340-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>In this paper, we give some existence theorems of solutions to <span>\\\\(\\\\Gamma \\\\)</span>-robust counterparts of gap function formulations of uncertain linear complementarity problems, in which <span>\\\\(\\\\Gamma \\\\)</span> plays a role in adjusting the robustness of the model against the level of conservatism of solutions. If the <span>\\\\(\\\\Gamma \\\\)</span>-robust uncertainty set is nonconvex, it is hard to prove the existence of solutions to the corresponding robust counterpart. Using techniques of asymptotic functions, we establish existence theorems of solutions to the corresponding robust counterpart. For the case of nonconvex <span>\\\\(\\\\Gamma \\\\)</span>-robust ellipsoidal uncertainty sets, these existence results are not proved in the paper [Krebs et al., Int. Trans. Oper. Res. 29 (2022), pp. 417–441]; for the case of convex <span>\\\\(\\\\Gamma \\\\)</span>-robust ellipsoidal uncertainty sets, our existence theorems are obtained under the conditions which are much weaker than those in Krebs’ paper. Finally, a case study for the uncertain traffic equilibrium problem is considered to illustrate the effects of nonconvex uncertainty sets on the level of conservatism of robust solutions.\\n</p>\",\"PeriodicalId\":15961,\"journal\":{\"name\":\"Journal of Global Optimization\",\"volume\":\"55 2\",\"pages\":\"\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2023-11-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Global Optimization\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1007/s10898-023-01340-6\",\"RegionNum\":3,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Mathematics\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Global Optimization","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1007/s10898-023-01340-6","RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Mathematics","Score":null,"Total":0}
Existence of solutions to $$\Gamma $$ -robust counterparts of gap function formulations of uncertain LCPs with ellipsoidal uncertainty sets
In this paper, we give some existence theorems of solutions to \(\Gamma \)-robust counterparts of gap function formulations of uncertain linear complementarity problems, in which \(\Gamma \) plays a role in adjusting the robustness of the model against the level of conservatism of solutions. If the \(\Gamma \)-robust uncertainty set is nonconvex, it is hard to prove the existence of solutions to the corresponding robust counterpart. Using techniques of asymptotic functions, we establish existence theorems of solutions to the corresponding robust counterpart. For the case of nonconvex \(\Gamma \)-robust ellipsoidal uncertainty sets, these existence results are not proved in the paper [Krebs et al., Int. Trans. Oper. Res. 29 (2022), pp. 417–441]; for the case of convex \(\Gamma \)-robust ellipsoidal uncertainty sets, our existence theorems are obtained under the conditions which are much weaker than those in Krebs’ paper. Finally, a case study for the uncertain traffic equilibrium problem is considered to illustrate the effects of nonconvex uncertainty sets on the level of conservatism of robust solutions.
期刊介绍:
The Journal of Global Optimization publishes carefully refereed papers that encompass theoretical, computational, and applied aspects of global optimization. While the focus is on original research contributions dealing with the search for global optima of non-convex, multi-extremal problems, the journal’s scope covers optimization in the widest sense, including nonlinear, mixed integer, combinatorial, stochastic, robust, multi-objective optimization, computational geometry, and equilibrium problems. Relevant works on data-driven methods and optimization-based data mining are of special interest.
In addition to papers covering theory and algorithms of global optimization, the journal publishes significant papers on numerical experiments, new testbeds, and applications in engineering, management, and the sciences. Applications of particular interest include healthcare, computational biochemistry, energy systems, telecommunications, and finance. Apart from full-length articles, the journal features short communications on both open and solved global optimization problems. It also offers reviews of relevant books and publishes special issues.