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Two measures of difficulty

Page, Scott E. (1996) Two measures of difficulty. Economic Theory, 8 (2). pp. 321-346. ISSN 0938-2259. https://resolver.caltech.edu/CaltechAUTHORS:20170821-135134067

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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.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1007/BF01211821DOIArticle
https://link.springer.com/article/10.1007%2FBF01211821PublisherArticle
http://resolver.caltech.edu/CaltechAUTHORS:20170818-133754197Related ItemWorking Paper
Additional Information:© 1996 Springer-Verlag. This paper has benefited from comments by seminar participants the NBER\CEME Decentralization Conference, UC-Irvine, and UC-San Diego. The author would like to thank Stan Reiter for his guidance and for his many suggestions in helping refine the concepts developed in this paper. Art Devany, Gordon Green, Jim Jordan, Nick Vriend, and an anonymous referee made helpful comments on earlier versions of this paper.
Issue or Number:2
Classification Code:JEL: O22
Record Number:CaltechAUTHORS:20170821-135134067
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20170821-135134067
Official Citation:Page, S.E. Econ Theory (1996) 8: 321. https://doi.org/10.1007/BF01211821
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:80647
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:21 Aug 2017 21:19
Last Modified:03 Oct 2019 18:33

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