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GECCO
2004
Springer
15 years 3 months ago
How Are We Doing? Predicting Evolutionary Algorithm Performance
Abstract. Given an evolutionary algorithm for a problem and an instance of the problem, the results of several trials of the EA on the instance constitute a sample from the distrib...
Mark A. Renslow, Brenda Hinkemeyer, Bryant A. Juls...
GECCO
2004
Springer
107views Optimization» more  GECCO 2004»
15 years 3 months ago
An Evolution Strategy Using a Continuous Version of the Gray-Code Neighbourhood Distribution
Abstract. We derive a continuous probability distribution which generates neighbours of a point in an interval in a similar way to the bitwise mutation of a Gray code binary string...
Jonathan E. Rowe, Dzena Hidovic
77
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GECCO
2004
Springer
166views Optimization» more  GECCO 2004»
15 years 3 months ago
An Effective Chromosome Representation for Evolving Flexible Job Shop Schedules
As the Flexible Job Shop Scheduling Problem (or FJSP) is strongly NP-hard, using an evolutionary approach to find near-optimal solutions requires effective chromosome representatio...
Joc Cing Tay, Djoko Wibowo
GECCO
2004
Springer
130views Optimization» more  GECCO 2004»
15 years 3 months ago
The Shifting Balance Genetic Algorithm as More than Just Another Island Model GA
The Shifting Balance Genetic Algorithm (SBGA) is an extension of the Genetic Algorithm (GA) that was created to promote guided diversity to improve performance in highly multimodal...
Mark Wineberg, Jun Chen
GECCO
2004
Springer
15 years 3 months ago
Introducing Subchromosome Representations to the Linkage Learning Genetic Algorithm
This paper introduces subchromosome representations to the linkage learning genetic algorithm (LLGA). The subchromosome representation is utilized for effectively lowering the num...
Ying-Ping Chen, David E. Goldberg