ACM Home Page
Please provide us with feedback. Feedback
Topological crossover for the permutation representation
Full text PdfPdf (138 KB)
Source Genetic And Evolutionary Computation Conference archive
Proceedings of the 2005 workshops on Genetic and evolutionary computation table of contents
Washington, D.C.
SESSION: TheoryRep contributions table of contents
Pages: 332 - 338  
Year of Publication: 2005
Authors
Alberto Moraglio  University of Essex, Wivenhoe Park, Colchester, UK
Riccardo Poli  University of Essex, Wivenhoe Park, Colchester, UK
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 8,   Downloads (12 Months): 46,   Citation Count: 6
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1102256.1102330
What is a DOI?

ABSTRACT

Topological crossovers are a class of representation-independent operators that are well-defined once a notion of distance over the solution space is defined. In this paper we explore how the topological framework applies to the permutation representation and in particular analyze the consequences of having more than one notion of distance available. Also, we study the interactions among distances and build a rational picture in which pre-existing recombination/crossover operators for permutation fit naturally. Lastly, we also analyze the application of topological crossover to TSP.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Bäck T, Fogel DB, Michalewicz Z (2000) Evolutionary Computation 1: Basic Algorithms and Operators. IOP Publishing, Bristol, UKT.
 
2
3
 
4
Deza M and Huang T (1998) Metrics on permutations, a survey, J. Combinatorics, Information and System Sciences 23, pages 173--185.
 
5
Fox B R and McMahon M B (1991) Genetic Operators for Sequencing Problems In G J E Rawlins, editor, Foundations of Genetic Algorithms, pages 284--300. Morgan Kaufmann.
 
6
Glover F and Kochenberger G (2002) Handbook of Metaheuristics. Kluwer Academic.
 
7
 
8
Kececioglu J and Sankoff D (1995) Exact and approximate algorithms for sorting by reversals, with applications to genome rearrangement. Algorithmica, 13, pages 180--210.
 
9
Moraglio A and Poli R (2004) Topological interpretation of crossover. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2004), pages 1377--1388.
 
10
Radcliffe N J (1992) Nonlinear genetic representations. In R. Manner and B. Manderick, editors, Proceedings of the 2 nd Conference on Parallel Problems Solving from Nature, pages 259--268. Morgan Kaufmann.
 
11
Radcliffe N J (1994) The Algebra of Genetic Algorithms, Annals of Maths and Artificial Intelligence 10, pages 339--384.
 
12
Solomon A, Sutcliffe P, Lister R (2003) Sorting Circular Permutations by Reversals. WADS 2003, pages 319--328
 
13


Collaborative Colleagues:
Alberto Moraglio: colleagues
Riccardo Poli: colleagues