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IPPS
2000
IEEE
13 years 11 months ago
A Parallel Co-evolutionary Metaheuristic
In order to show that the parallel co-evolution of di erent heuristic methods may lead to an e cient search strategy, we have hybridized three heuristic agents of complementary beh...
Vincent Bachelet, El-Ghazali Talbi
GECCO
2007
Springer
135views Optimization» more  GECCO 2007»
14 years 26 days ago
A cumulative evidential stopping criterion for multiobjective optimization evolutionary algorithms
In this work we present a novel and efficient algorithm– independent stopping criterion, called the MGBM criterion, suitable for Multiobjective Optimization Evolutionary Algorit...
Luis Martí, Jesús García, Ant...
PPSN
2004
Springer
14 years 1 days ago
The Application of Bayesian Optimization and Classifier Systems in Nurse Scheduling
Two ideas taken from Bayesian optimization and classifier systems are presented for personnel scheduling based on choosing a suitable scheduling rule from a set for each person’s...
Jingpeng Li, Uwe Aickelin
EPS
1998
Springer
13 years 11 months ago
Acquisition of General Adaptive Features by Evolution
We investigate the following question. Do populations of evolving agents adapt only to their recent environment or do general adaptive features appear over time? We find statistica...
Dan Ashlock, John E. Mayfield
GECCO
2010
Springer
191views Optimization» more  GECCO 2010»
13 years 6 months ago
Fitness importance for online evolution
To complement standard fitness functions, we propose "Fitness Importance" (FI) as a novel meta-heuristic for online learning systems. We define FI and show how it can be...
Philip Valencia, Raja Jurdak, Peter Lindsay