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GECCO
2003
Springer
137views Optimization» more  GECCO 2003»
14 years 21 days ago
The Spatially-Dispersed Genetic Algorithm
Abstract. Spatially structured population models improve the performance of genetic algorithms by assisting the selection scheme in maintaining diversity. A significant concern wi...
Grant Dick
GECCO
2003
Springer
14 years 21 days ago
Enhancing the Performance of GP Using an Ancestry-Based Mate Selection Scheme
The performance of genetic programming relies mostly on population-contained variation. If the population diversity is low then there will be a greater chance of the algorithm bein...
Rodney Fry, Andrew M. Tyrrell
GECCO
2003
Springer
14 years 21 days 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
GECCO
2003
Springer
415views Optimization» more  GECCO 2003»
14 years 21 days ago
Evolutionary Algorithms for Two Problems from the Calculus of Variations
Abstract. A brachistochrone is the path along which a weighted particle falls most quickly from one point to another, and a catenary is the smooth curve connecting two points whose...
Bryant A. Julstrom
GECCO
2003
Springer
132views Optimization» more  GECCO 2003»
14 years 21 days ago
Evolutionary Multimodal Optimization Revisited
Abstract. We revisit a class of multimodal function optimizations using evolutionary algorithms reformulated into a multiobjective framework where previous implementations have nee...
Rajeev Kumar, Peter Rockett