An abstract model for branch and cut

成果类型:
Article
署名作者:
Kazachkov, Aleksandr M.; Le Bodic, Pierre; Sankaranarayanan, Sriram
署名单位:
State University System of Florida; University of Florida; Monash University; Indian Institute of Management (IIM System); Indian Institute of Management Ahmedabad
刊物名称:
MATHEMATICAL PROGRAMMING
ISSN/ISSBN:
0025-5610
DOI:
10.1007/s10107-023-01991-z
发表日期:
2024
页码:
175-202
关键词:
摘要:
Branch and cut is the dominant paradigm for solving a wide range of mathematical programming problems-linear or nonlinear-combining efficient search (via branch and bound) and relaxation-tightening procedures (via cutting planes, or cuts). While there is a wealth of computational experience behind existing cutting strategies, there is simultaneously a relative lack of theoretical explanations for these choices, and for the tradeoffs involved therein. Recent papers have explored abstract models for branching and for comparing cuts with branch and bound. However, to model practice, it is crucial to understand the impact of jointly considering branching and cutting decisions. In this paper, we provide a framework for analyzing how cuts affect the size of branch-and-cut trees, as well as their impact on solution time. Our abstract model captures some of the key characteristics of real-world phenomena in branch-and-cut experiments, regarding whether to generate cuts only at the root or throughout the tree, how many rounds of cuts to add before starting to branch, and why cuts seem to exhibit nonmonotonic effects on the solution process.
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