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GECCO
2006
Springer
148views Optimization» more  GECCO 2006»
9 years 10 months ago
Behavioural GP diversity for dynamic environments: an application in hedge fund investment
We present a new mechanism for preserving phenotypic behavioural diversity in a Genetic Programming application for hedge fund portfolio optimization, and provide experimental res...
Wei Yan, Christopher D. Clack
GECCO
2006
Springer
287views Optimization» more  GECCO 2006»
9 years 10 months ago
A GA-ACO-local search hybrid algorithm for solving quadratic assignment problem
In recent decades, many meta-heuristics, including genetic algorithm (GA), ant colony optimization (ACO) and various local search (LS) procedures have been developed for solving a...
Yiliang Xu, Meng-Hiot Lim, Yew-Soon Ong, Jing Tang
GECCO
2006
Springer
152views Optimization» more  GECCO 2006»
9 years 10 months ago
Strong recombination, weak selection, and mutation
We show that there are unimodal fitness functions and genetic algorithm (GA) parameter settings where the GA, when initialized with a random population, will not move close to the...
Alden H. Wright, J. Neal Richter
GECCO
2006
Springer
162views Optimization» more  GECCO 2006»
9 years 10 months ago
Algebraic simplification of GP programs during evolution
Program bloat is a fundamental problem in the field of Genetic Programming (GP). Exponential growth of redundant and functionally useless sections of programs can quickly overcome...
Phillip Wong, Mengjie Zhang
GECCO
2006
Springer
161views Optimization» more  GECCO 2006»
9 years 10 months ago
The LEM3 implementation of learnable evolution model and its testing on complex function optimization problems
1 Learnable Evolution Model (LEM) is a form of non-Darwinian evolutionary computation that employs machine learning to guide evolutionary processes. Its main novelty are new type o...
Janusz Wojtusiak, Ryszard S. Michalski
GECCO
2006
Springer
123views Optimization» more  GECCO 2006»
9 years 10 months ago
Fluctuating crosstalk, deterministic noise, and GA scalability
This paper extends previous work showing how fluctuating crosstalk in a deterministic fitness function introduces noise into genetic algorithms. In that work, we modeled fluctuati...
Paul Winward, David E. Goldberg
GECCO
2006
Springer
173views Optimization» more  GECCO 2006»
9 years 10 months ago
Sets of receiver operating characteristic curves and their use in the evaluation of multi-class classification
Within the last two decades, Receiver Operating Characteristic (ROC) Curves have become a standard tool for the analysis and comparison of classifiers since they provide a conveni...
Stephan M. Winkler, Michael Affenzeller, Stefan Wa...
GECCO
2006
Springer
132views Optimization» more  GECCO 2006»
9 years 10 months ago
The role of diverse populations in phylogenetic analysis
The most popular approaches for reconstructing phylogenetic trees attempt to solve NP-hard optimization criteria such as maximum parsimony (MP). Currently, the bestperforming heur...
Tiffani L. Williams, Marc L. Smith
GECCO
2006
Springer
181views Optimization» more  GECCO 2006»
9 years 10 months ago
Robustness in cooperative coevolution
Though recent analysis of traditional cooperative coevolutionary algorithms (CCEAs) casts doubt on their suitability for static optimization tasks, our experience is that the algo...
R. Paul Wiegand, Mitchell A. Potter
GECCO
2006
Springer
205views Optimization» more  GECCO 2006»
9 years 10 months ago
Alternative evolutionary algorithms for evolving programs: evolution strategies and steady state GP
In contrast with the diverse array of genetic algorithms, the Genetic Programming (GP) paradigm is usually applied in a relatively uniform manner. Heuristics have developed over t...
L. Darrell Whitley, Marc D. Richards, J. Ross Beve...
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