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GECCO
2003
Springer
15 years 11 months ago
A Kernighan-Lin Local Improvement Heuristic That Solves Some Hard Problems in Genetic Algorithms
We present a Kernighan-Lin style local improvement heuristic for genetic algorithms. We analyze the run-time cost of the heuristic. We demonstrate through experiments that the heur...
William A. Greene
EVOW
2004
Springer
15 years 12 months ago
Constructing Dynamic Optimization Test Problems Using the Multi-objective Optimization Concept
Abstract. Dynamic optimization using evolutionary algorithms is receiving increasing interests. However, typical test functions for comparing the performance of various dynamic opt...
Yaochu Jin, Bernhard Sendhoff
NC
2002
210views Neural Networks» more  NC 2002»
15 years 6 months ago
Recent approaches to global optimization problems through Particle Swarm Optimization
This paper presents an overview of our most recent results concerning the Particle Swarm Optimization (PSO) method. Techniques for the alleviation of local minima, and for detectin...
Konstantinos E. Parsopoulos, Michael N. Vrahatis
GECCO
2009
Springer
16 years 1 months ago
Optimal robust expensive optimization is tractable
Following a number of recent papers investigating the possibility of optimal comparison-based optimization algorithms for a given distribution of probability on fitness functions...
Philippe Rolet, Michèle Sebag, Olivier Teyt...
AHS
2006
IEEE
119views Hardware» more  AHS 2006»
16 years 17 days ago
Particle Swarm Optimization with Discrete Recombination: An Online Optimizer for Evolvable Hardware
Self-reconfigurable adaptive systems have the possibility of adapting their own hardware configuration. This feature provides enhanced performance and flexibility, reflected i...
Jorge Peña, Andres Upegui, Eduardo Sanchez