Further results on an abstract model for branching and its application to mixed integer programming
| Autor: | Kerri Morgan, Pierre Le Bodic, Daniel Anderson |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Mathematical optimization
021103 operations research Branch and bound Computer science General Mathematics 0211 other engineering and technologies Feature selection 010103 numerical & computational mathematics 02 engineering and technology Solver 01 natural sciences Branching (linguistics) Optimization and Control (math.OC) 90C11 68Q25 FOS: Mathematics 0101 mathematics Mathematics - Optimization and Control Integer programming Software |
| Zdroj: | Mathematical Programming. 190:811-841 |
| ISSN: | 1436-4646 0025-5610 |
| Popis: | A key ingredient in branch and bound (B&B) solvers for mixed-integer programming (MIP) is the selection of branching variables since poor or arbitrary selection can affect the size of the resulting search trees by orders of magnitude. A recent article by Le Bodic and Nemhauser [Mathematical Programming, (2017)] investigated variable selection rules by developing a theoretical model of B&B trees from which they developed some new, effective scoring functions for MIP solvers. In their work, Le Bodic and Nemhauser left several open theoretical problems, solutions to which could guide the future design of variable selection rules. In this article, we first solve many of these open theoretical problems. We then implement an improved version of the model-based branching rules in SCIP 6.0, a state-of-the-art academic MIP solver, in which we observe an 11% geometric average time and node reduction on instances of the MIPLIB 2017 Benchmark Set that require large B&B trees. |
| Databáze: | OpenAIRE |
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