TGA: A new integrated approach to evolutionary algorithms

Proceedings of the IEEE Conference on Evolutionary Computation, ICEC

Volumn 2, Issue , 2001, Pages 917-924

  Ting, C K ^a   Li, S T ^a   Lee, C ^a  

^a NATIONAL SUN YAT SEN UNIVERSITY   (Taiwan)

Author keywords

[No Author keywords available]

Indexed keywords

BENCHMARKING; CORRELATION METHODS; HEURISTIC METHODS; OPTIMIZATION; POPULATION STATISTICS;

TABU SEARCH (TS);

GENETIC ALGORITHMS;

EID: 0034874136     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (22)

1. Degree of population diversity - A perspective on premature convergence in genetic algorithms and its Markov chain analysis
2. A synergetic approach to genetic algorithms for solving traveling salesman problem
3. Fuzzy connectives based crossover operators to model genetic algorithms population diversity
4. A functional specialization hypothesis for designing genetic algorithms
5. A greedy genetic algorithm for the quadratic assignment problem
6. An eugenic mutations for optimum problems
7. DCGA: A diversity control oriented genetic algorithm
8. New selection method to improve the population diversity in genetic algorithms
9. A thermodynamical selection rule for the genetic algorithm
10. Genetic algorithms and tabu search: Hybrid for optimization
11. A hybrid heuristic for the uncapacitated hub location problem
12. Integrating genetic algorithms, tabu search, and simulated annealing for the unit commitment problem
13. A hybrid genetic algorithm for the open shop scheduling problem
14. Genetic algorithm for power systems planning
15. Hybrid heuristics for the capacitated lot sizing and loading problem with setup times and overtime decisions
16. A new GA approach for the vehicle routing problem
17. A tabu search-based algorithm for the fuzzy clustering problem