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Two measures of difficulty (*)

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Author Info
Scott E. Page (Division of Humanities and Social Sciences 228-77, California Institute of Technology, Pasadena, CA 91125, USA)
Abstract

The paper constructs two measures of difficulty for functions defined over binary strings. The first of these measures, cover size, captures the difficulty of solving a problem in parallel. The second measure, ascent size, captures the difficulty of solving a problem sequentially. We show how these measures can help us to better understand the performance of genetic algorithms and simulated annealing, two widely used search algorithms. We also show how disparities in these two measures may shed light on the organizational structure of firms.

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Publisher Info
Article provided by Springer in its journal Economic Theory.

Volume (Year): 8 (1996)
Issue (Month): 2 ()
Pages: 321-346
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Handle: RePEc:spr:joecth:v:8:y:1996:i:2:p:321-346

Note: Received: October 31, 1994; revised version December 7, 1994
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