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The no free lunch and realistic search algorithms

Authors:

Yossi Borenstein,

Riccardo PoliAuthors Info & Claims

GECCO '06: Proceedings of the 8th annual conference on Genetic and evolutionary computation

Pages 1399 - 1400

https://doi.org/10.1145/1143997.1144214

Published: 08 July 2006 Publication History

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Abstract

The No-Free-Lunch theorems (NFLTs) are criticized for being too general to be of any relevance to the real world scenario. This paper investigates, both formally and empirically, the implications of the NFLTs for realistic search algorithms. In the first part of the paper, by restricting ourselves to a specific performance measure, we derive a new NFL result for a class of problems which is not closed under permutations. In the second part, we discuss properties of this set which are likely to be true for realistic search algorithms. We provide empirical support for this in [1].

References

[1]

Yossi Borenstein and Riccardo Poli. The no free lunch and realistic search algorithms. Technical report, University of Essex, 2006.

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[2]

David Wolpert and William G. Macready. No free lunch theorems for optimization. IEEE Trans. Evolutionary Computation, 1(1):67--82, 1997.

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[3]

C. Schumacher, M. D. Vose, and L. D. Whitley. The no free lunch and problem description length. In Lee Spector et al. editors, GECCO 2001. Morgan Kaufmann.

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The no free lunch and realistic search algorithms
1. Theory of computation
  1. Design and analysis of algorithms

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GECCO '06: Proceedings of the 8th annual conference on Genetic and evolutionary computation

July 2006

2004 pages

ISBN:1595931864

DOI:10.1145/1143997

General Chair:
Mike Cattolico
Tiger Mountain Scientific, Inc., USA

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 08 July 2006

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GECCO06: Genetic and Evolutionary Computation Conference

July 8 - 12, 2006

Washington, Seattle, USA

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GECCO '06 Paper Acceptance Rate 205 of 446 submissions, 46%;

Overall Acceptance Rate 1,669 of 4,410 submissions, 38%

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A probabilistic reformulation of no free lunch: Continuous lunches are not free

When and Why Metaheuristics Researchers can Ignore “No Free Lunch” Theorems

Conditions that Obviate the No-Free-Lunch Theorems for Optimization

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A probabilistic reformulation of no free lunch: Continuous lunches are not free

When and Why Metaheuristics Researchers can Ignore “No Free Lunch” Theorems

Conditions that Obviate the No-Free-Lunch Theorems for Optimization

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