See this document in CiteSeerX!

CEC-2005, Edinburgh, 2-5 September 2005, Vol 1 pp81-88, IEEE press Revision : 1.19a (2005)  (Make Corrections)  
Evolving Problems to Learn about Particle Swarm and other Optimisers W. B....



  Home/Search   Context   Related

 
View or download:
cs.ucl.ac.uk/staff/...wbl_cec2005.ps.gz
Cached:  PS.gz  PS  PDF   Image  Update  Help

From:  cs.ucl.ac.uk/staff/W.Langdon/f... (more)
(Enter author homepages)

Rate this article: (best)
  Comment on this article  
(Enter summary)

Abstract: We use evolutionary computation (EC) to automatically find problems which demonstrate the strength and weaknesses of modern search heuristics. In particular we analyse Particle Swarm Optimization (PSO) and Differential Evolution (DE). Both evolutionary algorithms are contrasted with a robust deterministic gradient based searcher (based on Newton-Raphson). The fitness landscapes made by genetic programming (GP) are used to illustrate difficulties in GAs and PSOs thereby explaining how they work... (Update)

Active bibliography (related documents):   More   All
3.0:   Evolving Problems to Learn about Particle Swarm and other.. - Langdon, Poli (2005)   (Correct)
3.0:   CEC-2005, Edinburgh, 2-5 September 2005, Vol 1, pp81--88.. - Evolving Problems To (2005)   (Correct)
0.5:   Mixed Variable Non-Linear Optimization By Differential Evolution - Lampinen   (Correct)

Similar documents based on text:
0.0:   Unknown -   (Correct)

BibTeX entry:   (Update)

@misc{ to-cec,
  author = "Evolving Problems To",
  title = "CEC-2005, Edinburgh, 2-5 September 2005, Vol 1 pp81--88, IEEE press Revision
    : 1.19a",
  url = "citeseer.ist.psu.edu/759796.html" }
Citations (may not include all citations):
1053   Genetic Programming: On the Programming of Computers by Mean.. (context) - Koza - 1992
76   A study of reproduction in generational and steady state gen.. (context) - Syswerda - 1991
73   Swarm Intelligence (context) - Kennedy, Eberhart - 2001
70   Foundations of Genetic Programming (context) - Langdon, Poli - 2002
34   Differential evolution - a simple and efficient adaptive sch.. - Storn, Price - 1995
24   Evolutionary computation at the edge of feasibility - Schoenauer, Michalewicz - 1996
23   Genetic Programming and Data Structures - Langdon - 1998
11   An introduction to differential evolution (context) - Price - 1999
10   IEEE Transactions on Evolutionary Computation (context) - Clerc, Kennedy et al. - 2002
10   Differential evolution (context) - Storn - 2005
9   The behavior of particles (context) - Kennedy - 1998
6   Particle swarm optimization: Surfing the waves - Ozcan, Mohan - 1999
6   Mechanical engineering design optimization by differential e.. (context) - Lampinen, Zelinka - 1999
5   An Analysis of Particle Swarm Optimizers (context) - van den Bergh - 2001
4   Designing digital filters with differential evolution (context) - Storn - 1999
3   competition at http://cswww (context) - Poli, TinyGP - 2004
3   DeApp - an application in java for the usage of differential.. - Storn - 1999
3   On stagnation of the differential evolution algorithm - Lampinen, Zelinka - 2000
3   Understanding particle swarm optimisation by evolving proble.. (context) - Langdon, Poli et al. - 2005
3   Control of population diversity and adaptation in differenti.. (context) - Zaharie - 2003

Documents on the same site (http://www.cs.ucl.ac.uk/staff/W.Langdon/ftp/papers/):   More
A Model Of Landscapes - Jones (1994)   (Correct)
The Application of Genetic Programming for Feature Construction.. - Muharram (2005)   (Correct)
GP-COM: A Distributed, Component-Based Genetic Programming.. - Harris, Buxton   (Correct)

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC