{"title":"Generalized min-up/min-down polytopes","authors":"Cécile Rottner","doi":"10.1016/j.disopt.2024.100866","DOIUrl":null,"url":null,"abstract":"<div><div>Consider a time horizon and a set of <span><math><mi>N</mi></math></span> possible states for a given system. The system must be in exactly one state at a time. In this paper, we generalize classical results on min-up/min-down constraints for a 2-state system to an <span><math><mi>N</mi></math></span>-state system with <span><math><mrow><mi>N</mi><mo>≥</mo><mn>3</mn></mrow></math></span>. The minimum-time constraints enforce that if the system switches to state <span><math><mi>i</mi></math></span> at time <span><math><mi>t</mi></math></span>, then it must remain in state <span><math><mi>i</mi></math></span> for a minimum number of time steps. The minimum-time polytope is defined as the convex hull of integer solutions satisfying the minimum-time constraints. A variant of minimum-time constraints is also considered, namely the no-spike constraints. They enforce that if state <span><math><mi>i</mi></math></span> is switched on at time <span><math><mi>t</mi></math></span>, the system must remain on states <span><math><mrow><mi>j</mi><mo>≥</mo><mi>i</mi></mrow></math></span> during a minimum time. Symmetrically, they also enforce that if state <span><math><mi>i</mi></math></span> is switched off at time <span><math><mi>t</mi></math></span>, the system must remain on states <span><math><mrow><mi>j</mi><mo><</mo><mi>i</mi></mrow></math></span> during a minimum time. The no-spike polytope is defined as the convex hull of integer solutions satisfying the no-spike constraints. For both the minimum-time polytope and the no-spike polytope, we introduce families of valid inequalities. We prove that these inequalities are facet-defining and lead to a complete description of polynomial size for each polytope.</div></div>","PeriodicalId":50571,"journal":{"name":"Discrete Optimization","volume":"55 ","pages":"Article 100866"},"PeriodicalIF":0.9000,"publicationDate":"2024-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Discrete Optimization","FirstCategoryId":"100","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1572528624000458","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MATHEMATICS, APPLIED","Score":null,"Total":0}
引用次数: 0
Abstract
Consider a time horizon and a set of possible states for a given system. The system must be in exactly one state at a time. In this paper, we generalize classical results on min-up/min-down constraints for a 2-state system to an -state system with . The minimum-time constraints enforce that if the system switches to state at time , then it must remain in state for a minimum number of time steps. The minimum-time polytope is defined as the convex hull of integer solutions satisfying the minimum-time constraints. A variant of minimum-time constraints is also considered, namely the no-spike constraints. They enforce that if state is switched on at time , the system must remain on states during a minimum time. Symmetrically, they also enforce that if state is switched off at time , the system must remain on states during a minimum time. The no-spike polytope is defined as the convex hull of integer solutions satisfying the no-spike constraints. For both the minimum-time polytope and the no-spike polytope, we introduce families of valid inequalities. We prove that these inequalities are facet-defining and lead to a complete description of polynomial size for each polytope.
期刊介绍:
Discrete Optimization publishes research papers on the mathematical, computational and applied aspects of all areas of integer programming and combinatorial optimization. In addition to reports on mathematical results pertinent to discrete optimization, the journal welcomes submissions on algorithmic developments, computational experiments, and novel applications (in particular, large-scale and real-time applications). The journal also publishes clearly labelled surveys, reviews, short notes, and open problems. Manuscripts submitted for possible publication to Discrete Optimization should report on original research, should not have been previously published, and should not be under consideration for publication by any other journal.