{"title":"数学优化问题的混合障碍-惩罚方法的构造全局收敛性","authors":"Porfirio Suñagua, A. Oliveira","doi":"10.1590/0101-7438.2020.040.00217467","DOIUrl":null,"url":null,"abstract":". In this paper we develop a generic mixed bi-parametric barrier-penalty method based upon barrier and penalty generic algorithms for constrained nonlinear programming problems. When the feasible set is defined by equality and inequality functional constraints, it is possible to provide an explicit barrier and penalty functions. If such case, the continuity and differentiable properties of the restrictions and objective functions could be inherited to the penalized function. The main contribution of this work is a constructive proof for the global convergence of the sequence generated by the proposed mixed method. The proof uses separately the main results of global convergence of barrier and penalty methods. Finally, for some simple nonlinear problem, we deduce explicitly the mixed barrier–penalty function and illustrate all functions defined in this work. Also we implement MATLAB code for generate iterative points for the mixed method.","PeriodicalId":35341,"journal":{"name":"Pesquisa Operacional","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A CONSTRUCTIVE GLOBAL CONVERGENCE OF THE MIXED BARRIER-PENALTY METHOD FOR MATHEMATICAL OPTIMIZATION PROBLEMS\",\"authors\":\"Porfirio Suñagua, A. Oliveira\",\"doi\":\"10.1590/0101-7438.2020.040.00217467\",\"DOIUrl\":null,\"url\":null,\"abstract\":\". In this paper we develop a generic mixed bi-parametric barrier-penalty method based upon barrier and penalty generic algorithms for constrained nonlinear programming problems. When the feasible set is defined by equality and inequality functional constraints, it is possible to provide an explicit barrier and penalty functions. If such case, the continuity and differentiable properties of the restrictions and objective functions could be inherited to the penalized function. The main contribution of this work is a constructive proof for the global convergence of the sequence generated by the proposed mixed method. The proof uses separately the main results of global convergence of barrier and penalty methods. Finally, for some simple nonlinear problem, we deduce explicitly the mixed barrier–penalty function and illustrate all functions defined in this work. Also we implement MATLAB code for generate iterative points for the mixed method.\",\"PeriodicalId\":35341,\"journal\":{\"name\":\"Pesquisa Operacional\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Pesquisa Operacional\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1590/0101-7438.2020.040.00217467\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Decision Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pesquisa Operacional","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1590/0101-7438.2020.040.00217467","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Decision Sciences","Score":null,"Total":0}
A CONSTRUCTIVE GLOBAL CONVERGENCE OF THE MIXED BARRIER-PENALTY METHOD FOR MATHEMATICAL OPTIMIZATION PROBLEMS
. In this paper we develop a generic mixed bi-parametric barrier-penalty method based upon barrier and penalty generic algorithms for constrained nonlinear programming problems. When the feasible set is defined by equality and inequality functional constraints, it is possible to provide an explicit barrier and penalty functions. If such case, the continuity and differentiable properties of the restrictions and objective functions could be inherited to the penalized function. The main contribution of this work is a constructive proof for the global convergence of the sequence generated by the proposed mixed method. The proof uses separately the main results of global convergence of barrier and penalty methods. Finally, for some simple nonlinear problem, we deduce explicitly the mixed barrier–penalty function and illustrate all functions defined in this work. Also we implement MATLAB code for generate iterative points for the mixed method.
Pesquisa OperacionalDecision Sciences-Management Science and Operations Research
CiteScore
1.60
自引率
0.00%
发文量
19
审稿时长
8 weeks
期刊介绍:
Pesquisa Operacional is published each semester by the Sociedade Brasileira de Pesquisa Operacional - SOBRAPO, performing one volume per year, and is distributed free of charge to its associates. The abbreviated title of the journal is Pesq. Oper., which should be used in bibliographies, footnotes and bibliographical references and strips.