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IJCAI
1993
14 years 11 months ago
Evolutionary Learning Strategy using Bug-Based Search
We introduce a new approach to GA (Genetic Algorithms) based problem solving. Earlier GAs did not contain local search (i.e. hill climbing) mechanisms, which led to optimization d...
Hitoshi Iba, Tetsuya Higuchi, Hugo de Garis, Taisu...
GECCO
2004
Springer
147views Optimization» more  GECCO 2004»
15 years 3 months ago
A Demonstration of Neural Programming Applied to Non-Markovian Problems
Genetic programming may be seen as a recent incarnation of a long-held goal in evolutionary computation: to develop actual computational devices through evolutionary search. Geneti...
Gabriel Catalin Balan, Sean Luke
PPSN
2000
Springer
15 years 1 months ago
Real-Coded Adaptive Range Genetic Algorithm Applied to Transonic Wing Optimization
Real-coded Adaptive Range Genetic Algorithms (ARGAs) have been applied to a practical three-dimensional shape optimization for aerodynamic design of an aircraft wing. The real-code...
Akira Oyama, Shigeru Obayashi, Takashi Nakamura
GECCO
2007
Springer
183views Optimization» more  GECCO 2007»
15 years 3 months ago
A genetic algorithm for privacy preserving combinatorial optimization
We propose a protocol for a local search and a genetic algorithm for the distributed traveling salesman problem (TSP). In the distributed TSP, information regarding the cost funct...
Jun Sakuma, Shigenobu Kobayashi
MP
2006
137views more  MP 2006»
14 years 9 months ago
New algorithms for singly linearly constrained quadratic programs subject to lower and upper bounds
There are many applications related to singly linearly constrained quadratic programs subjected to upper and lower bounds. In this paper, a new algorithm based on secant approximat...
Yu-Hong Dai, Roger Fletcher