Exploiting Solving Phases for Mixed-Integer Programs

  • Modern MIP solving software incorporates dozens of auxiliary algorithmic components for supporting the branch-and-bound search in finding and improving solutions and in strengthening the relaxation. Intuitively, a dynamic solving strategy with an appropriate emphasis on different solving components and strategies is desirable during the search process. We propose an adaptive solver behavior that dynamically reacts on transitions between the three typical phases of a MIP solving process: The first phase objective is to find a feasible solution. During the second phase, a sequence of incumbent solutions gets constructed until the incumbent is eventually optimal. Proving optimality is the central objective of the remaining third phase. Based on the MIP-solver SCIP, we demonstrate the usefulness of the phase concept both with an exact recognition of the optimality of a solution, and provide heuristic alternatives to make use of the concept in practice.

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Metadaten
Author:Gregor Hendel
Document Type:In Proceedings
Parent Title (English):Operations Research Proceedings 2015
First Page:3
Last Page:9
Year of first publication:2016
Preprint:urn:nbn:de:0297-zib-57098
DOI:http://dx.doi.org/10.1007/978-3-319-42902-1_1

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