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Using diversification, communication and parallelism to solve mixed-integer linear programs

Rodolfo Carvajal(rocarvaj***at***gatech.edu)
Shabbir Ahmed(sahmed***at***isye.gatech.edu)
George Nemhauser(george.nemhauser***at***isye.gatech.edu)
Kevin Furman(kevin.c.furman***at***exxonmobil.com)
Vikas Goel(vikas.goel***at***exxonmobil.com)
Yufen Shao(yufen.shao***at***exxonmobil.com)

Abstract: Performance variability of modern mixed-integer programming solvers and possible ways of exploiting this phenomenon present an interesting opportunity in the development of algorithms to solve mixed-integer linear programs (MILPs). We propose a framework using multiple branch-and-bound trees to solve MILPs while allowing them to share information in a parallel execution. We present computational results on instances from MIPLIB 2010 illustrating the benefits of this framework.

Keywords: Integer programming, branch-and-bound, diversification, communication, parallelism, performance variability

Category 1: Integer Programming ((Mixed) Integer Linear Programming )

Category 2: Optimization Software and Modeling Systems (Parallel Algorithms )

Category 3: Optimization Software and Modeling Systems

Citation: Submitted to Elsevier, May 2013.

Download: [PDF]

Entry Submitted: 05/30/2013
Entry Accepted: 05/30/2013
Entry Last Modified: 05/30/2013

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