LP-based Genetic Algorithm for the Minimum Graph Bisection Problem

Michael Armbruster (), Marzena Fügenschuh (), Christoph Helmberg, Nikolay Jetchev and Alexander Martin
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Michael Armbruster: Chemnitz University of Technology
Marzena Fügenschuh: Darmstadt University of Technology
Christoph Helmberg: Chemnitz University of Technology
Nikolay Jetchev: Darmstadt University of Technology
Alexander Martin: Darmstadt University of Technology

A chapter in Operations Research Proceedings 2005, 2006, pp 315-320 from Springer

Abstract: Summary We investigate the minimum graph bisection problem concerning partitioning the nodes of a graph into two subsets such that the total weight of each set is within some lower and upper limits. The objective is to minimize the total cost of edges between both subsets of the partition. This problem has a variety of applications, for instance in the design of electronic circuits and in parallel computing. We present an integer linear programming formulation for this problem. We develop a primal heuristic based on a genetic algorithm, incorporate it in a branch-and-cut framework and present some computational results.

Keywords: Genetic Algorithm; Mutation Type; Valid Inequality; Graph Partitioning; Integer Linear Programming Formulation (search for similar items in EconPapers)
Date: 2006
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Persistent link: https://EconPapers.repec.org/RePEc:spr:oprchp:978-3-540-32539-0_50

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DOI: 10.1007/3-540-32539-5_50

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