Generating Applicable Synthetic Instances for Branch Problems

Leo Lopes () and Kate Smith-Miles ()
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Leo Lopes: SAS Institute, Cary, North Carolina 27513
Kate Smith-Miles: School of Mathematical Sciences, Monash University, Clayton, Victoria 3800, Australia

Operations Research, 2013, vol. 61, issue 3, 563-577

Abstract: Generating valid synthetic instances for branch problems---those that contain a core problem like knapsack or graph coloring, but add several complications---is hard. It is even harder to generate instances that are applicable to the specific goals of an experiment and help to support the claims made. This paper presents a methodology for tuning instance generators of branch problems so that synthetic instances are similar to real ones and are capable of eliciting different behaviors from solvers. A statistic is proposed to summarize the applicability of instances for drawing a valid conclusion. The methodology is demonstrated on the Udine timetabling problem. Examples and the necessary cyberinfrastructure are available as a project from Computational Infrastructure for Operations Research (COIN-OR).

Keywords: instance generation; data mining; optimization; timetabling (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (6)

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