Learning in Search

Philippe Refalo ()
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Philippe Refalo: IBM, Les Taissounieres

A chapter in Hybrid Optimization, 2011, pp 337-356 from Springer

Abstract: Abstract This chapter focuses on the recent improvements in solution search that are based on learning. We will describe some learning methods applied in areas such as mixed-integer programming, constraint programming, and those used for satisfaction problems. Instead of being exhaustive, we will concentrate on some of the most exciting advances. In particular, we will focus on pseudo-cost strategies used in general-purpose mixed-integer programming solvers, on the strategy learning used for automatic search in constraint programming, and on no-good generation in SAT solvers. Several examples are given to illustrate the effectiveness of learning in these areas. Some practical results are also given using the integration of different learning techniques.

Date: 2011
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Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-1-4419-1644-0_10

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DOI: 10.1007/978-1-4419-1644-0_10

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