Search-space smoothing for combinatorial optimization problems

Johannes Schneider, Markus Dankesreiter, Werner Fettes, Ingo Morgenstern, Martin Schmid and Johannes Maria Singer

Physica A: Statistical Mechanics and its Applications, 1997, vol. 243, issue 1, 77-112

Abstract: Commonly there are two types of local search approaches known to treat combinatorial optimization problems with very complex search-space structure: One is to introduce very complicated types of local move classes, allowing a bypass of high energetic barriers separating different minima. The second is introducing a control-parameter (i.e. temperature in physics terminology) dependent state space walker, which is — depending on this control parameter — more or less easily able to climb over barriers. A third, less well-known, but very obvious approach is to smooth the search space, i.e. to eliminate barriers between low-energy configurations and therefore to allow a fast and easy approach to the global optimum. This procedure will be discussed in depth in the following work.

Keywords: Optimization; Monte Carlo; Traveling salesman; Great deluge; Smoothing; Local search (search for similar items in EconPapers)
Date: 1997
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:243:y:1997:i:1:p:77-112

DOI: 10.1016/S0378-4371(97)00207-0

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