Using diversification, communication and parallelism to solve mixed-integer linear programs
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.
Entry Submitted: 05/30/2013
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