{"title":"退化单纯形轴的数目。","authors":"Kirill Kukharenko, Laura Sanità","doi":"10.1007/s10107-026-02349-x","DOIUrl":null,"url":null,"abstract":"<p><p>The simplex algorithm is one of the most popular algorithms to solve linear programs (LPs). Starting at an extreme point solution of an LP, it performs a sequence of basis exchanges (called pivots) that allows one to move to a better extreme point along an improving edge-direction of the underlying polyhedron. A key issue in the simplex algorithm's performance is <i>degeneracy</i>, which may lead to a (potentially long) sequence of basis exchanges which do not change the current extreme point solution. In this paper, we prove that one can employ any improving feasible direction at an extreme point to limit the number of consecutive degenerate pivots that the simplex algorithm performs to <math><mrow><mi>n</mi> <mo>-</mo> <mi>m</mi> <mo>-</mo> <mn>1</mn></mrow> </math> , where <i>n</i> is the number of variables and <i>m</i> is the number of equality constraints of a given LP in standard equality form.</p>","PeriodicalId":18297,"journal":{"name":"Mathematical Programming","volume":"216 1-2","pages":"757-791"},"PeriodicalIF":2.1000,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13368946/pdf/","citationCount":"0","resultStr":"{\"title\":\"On the number of degenerate simplex pivots.\",\"authors\":\"Kirill Kukharenko, Laura Sanità\",\"doi\":\"10.1007/s10107-026-02349-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The simplex algorithm is one of the most popular algorithms to solve linear programs (LPs). Starting at an extreme point solution of an LP, it performs a sequence of basis exchanges (called pivots) that allows one to move to a better extreme point along an improving edge-direction of the underlying polyhedron. A key issue in the simplex algorithm's performance is <i>degeneracy</i>, which may lead to a (potentially long) sequence of basis exchanges which do not change the current extreme point solution. In this paper, we prove that one can employ any improving feasible direction at an extreme point to limit the number of consecutive degenerate pivots that the simplex algorithm performs to <math><mrow><mi>n</mi> <mo>-</mo> <mi>m</mi> <mo>-</mo> <mn>1</mn></mrow> </math> , where <i>n</i> is the number of variables and <i>m</i> is the number of equality constraints of a given LP in standard equality form.</p>\",\"PeriodicalId\":18297,\"journal\":{\"name\":\"Mathematical Programming\",\"volume\":\"216 1-2\",\"pages\":\"757-791\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2026-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13368946/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Mathematical Programming\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1007/s10107-026-02349-x\",\"RegionNum\":2,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2026/3/23 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mathematical Programming","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1007/s10107-026-02349-x","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2026/3/23 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0
摘要
单纯形算法是求解线性规划最常用的算法之一。从LP的极值点解开始,它执行一系列基交换(称为枢轴),允许人们沿着底层多面体的改进边方向移动到更好的极值点。单纯形算法性能的一个关键问题是退化,这可能导致(潜在的)基交换序列,而这些序列不会改变当前的极值点解。本文证明了可以在极值点上使用任何改进可行方向将单纯形算法执行的连续退化轴数限制为n - m - 1,其中n为给定LP的变量数,m为标准等式形式的等式约束数。
The simplex algorithm is one of the most popular algorithms to solve linear programs (LPs). Starting at an extreme point solution of an LP, it performs a sequence of basis exchanges (called pivots) that allows one to move to a better extreme point along an improving edge-direction of the underlying polyhedron. A key issue in the simplex algorithm's performance is degeneracy, which may lead to a (potentially long) sequence of basis exchanges which do not change the current extreme point solution. In this paper, we prove that one can employ any improving feasible direction at an extreme point to limit the number of consecutive degenerate pivots that the simplex algorithm performs to , where n is the number of variables and m is the number of equality constraints of a given LP in standard equality form.
期刊介绍:
Mathematical Programming publishes original articles dealing with every aspect of mathematical optimization; that is, everything of direct or indirect use concerning the problem of optimizing a function of many variables, often subject to a set of constraints. This involves theoretical and computational issues as well as application studies. Included, along with the standard topics of linear, nonlinear, integer, conic, stochastic and combinatorial optimization, are techniques for formulating and applying mathematical programming models, convex, nonsmooth and variational analysis, the theory of polyhedra, variational inequalities, and control and game theory viewed from the perspective of mathematical programming.