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AAAI
2000
13 years 6 months ago
Dynamic Representations and Escaping Local Optima: Improving Genetic Algorithms and Local Search
Local search algorithms often get trapped in local optima. Algorithms such as tabu search and simulated annealing 'escape' local optima by accepting nonimproving moves. ...
Laura Barbulescu, Jean-Paul Watson, L. Darrell Whi...
SGAI
2007
Springer
13 years 10 months ago
Escaping Local Optima: Constraint Weights vs. Value Penalties
Constraint Satisfaction Problems can be solved using either iterative improvement or constructive search approaches. Iterative improvement techniques converge quicker than the cons...
Muhammed Basharu, Inés Arana, Hatem Ahriz
ECAI
2008
Springer
13 years 6 months ago
Structure Learning of Markov Logic Networks through Iterated Local Search
Many real-world applications of AI require both probability and first-order logic to deal with uncertainty and structural complexity. Logical AI has focused mainly on handling com...
Marenglen Biba, Stefano Ferilli, Floriana Esposito
CEC
2005
IEEE
13 years 10 months ago
Genetic algorithms with self-organized criticality for dynamic optimization problems
This paper proposes a genetic algorithm (GA) with random immigrants for dynamic optimization problems where the worst individual and its neighbours are replaced every generation. I...
Renato Tinós, Shengxiang Yang
GECCO
2005
Springer
140views Optimization» more  GECCO 2005»
13 years 10 months ago
Multi-niche crowding in the development of parallel genetic simulated annealing
In this paper, a new hybrid of genetic algorithm (GA) and simulated annealing (SA), referred to as GSA, is presented. In this algorithm, SA is incorporated into GA to escape from ...
Zhi-Gang Wang, Mustafizur Rahman 0002, Yoke-San Wo...