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» Evolutionary multiobjective optimization
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139
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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
120
Voted
GECCO
2006
Springer
129views Optimization» more  GECCO 2006»
15 years 6 months ago
Revisiting evolutionary algorithms with on-the-fly population size adjustment
In an evolutionary algorithm, the population has a very important role as its size has direct implications regarding solution quality, speed, and reliability. Theoretical studies ...
Fernando G. Lobo, Cláudio F. Lima
125
Voted
GECCO
2006
Springer
175views Optimization» more  GECCO 2006»
15 years 6 months ago
A computational theory of adaptive behavior based on an evolutionary reinforcement mechanism
Two mathematical and two computational theories from the field of human and animal learning are combined to produce a more general theory of adaptive behavior. The cornerstone of ...
J. J. McDowell, Paul L. Soto, Jesse Dallery, Saule...
126
Voted
GECCO
2008
Springer
143views Optimization» more  GECCO 2008»
15 years 3 months ago
A parallel evolutionary algorithm for unconstrained binary quadratic problems
In this paper an island model is described for the unconstrained Binary Quadratic Problem (BQP), which can be used with up to 2500 binary variables. Our island model uses a master...
István Borgulya
IJHIS
2006
94views more  IJHIS 2006»
15 years 2 months ago
A new fine-grained evolutionary algorithm based on cellular learning automata
In this paper, a new evolutionary computing model, called CLA-EC, is proposed. This model is a combination of a model called cellular learning automata (CLA) and the evolutionary ...
Reza Rastegar, Mohammad Reza Meybodi, Arash Hariri