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GECCO
2005
Springer
130views Optimization» more  GECCO 2005»
15 years 10 months ago
Quality-time analysis of multi-objective evolutionary algorithms
A quality-time analysis of multi-objective evolutionary algorithms (MOEAs) based on schema theorem and building blocks hypothesis is developed. A bicriteria OneMax problem, a hypo...
Jian-Hung Chen, Shinn-Ying Ho, David E. Goldberg
GECCO
2005
Springer
127views Optimization» more  GECCO 2005»
15 years 10 months ago
The enhanced evolutionary tabu search and its application to the quadratic assignment problem
We describe the Enhanced Evolutionary Tabu Search (EE-TS) local search technique. The EE-TS metaheuristic technique combines Reactive Tabu Search with evolutionary computing eleme...
John F. McLoughlin III, Walter Cedeño
GECCO
2006
Springer
129views Optimization» more  GECCO 2006»
15 years 8 months ago
Revisiting evolutionary algorithms with on-the-fly population size adjustment
In an evolutionary algorithm, the population has a very important role as its size has direct implications regarding solution quality, speed, and reliability. Theoretical studies ...
Fernando G. Lobo, Cláudio F. Lima
CEC
2010
IEEE
15 years 5 months ago
On the role of modularity in evolutionary dynamic optimisation
The field of evolutionary dynamic optimisation is concerned with the application of evolutionary algorithms to dynamic optimisation problems. In recent years, numerous new algorith...
Philipp Rohlfshagen, Xin Yao
GECCO
2008
Springer
120views Optimization» more  GECCO 2008»
15 years 5 months ago
A robust evolutionary framework for multi-objective optimization
Evolutionary multi-objective optimization (EMO) methodologies, suggested in the beginning of Nineties, focussed on the task of finding a set of well-converged and well-distribute...
Kalyanmoy Deb