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IJCAI
1993
15 years 4 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
2008
Springer
133views Optimization» more  GECCO 2008»
15 years 4 months ago
The micro-genetic operator in the search of global trends
This work studies the mGA operator (Micro Genetic Algorithm), that has been proposed in literature as a “local search” operator for optimization with Genetic Algorithm. A new ...
Flávio V. C. Martins, Eduardo G. Carrano, E...
GECCO
2010
Springer
213views Optimization» more  GECCO 2010»
15 years 3 months ago
Consultant-guided search algorithms for the quadratic assignment problem
Abstract. Consultant-Guided Search (CGS) is a recent swarm intelligence metaheuristic for combinatorial optimization problems, inspired by the way real people make decisions based ...
Serban Iordache
GECCO
2005
Springer
127views Optimization» more  GECCO 2005»
15 years 8 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
EOR
2007
90views more  EOR 2007»
15 years 3 months ago
Tabu search and GRASP for the maximum diversity problem
In this paper, we develop new heuristic procedures for the maximum diversity problem (MDP). This NPhard problem has a significant number of practical applications such as environm...
Abraham Duarte, Rafael Martí