Optimised Crossover Genetic Algorithms for Combinatorial Optimisation Problems
A Genetic Algorithm is successful in generating near -optimal solutions if it is able to produce o®spring during crossover that is better than the parent solutions. Most of the current methods of crossover determine o®spring by using a stochastic approach and without reference to the objective func...
Bewaard in:
Hoofdauteur: | Nazif, Habibeh |
---|---|
Formaat: | Thesis |
Taal: | English |
Gepubliceerd in: |
2010
|
Online toegang: | http://ethesis.upm.edu.my/id/eprint/6001/1/FS_2010_53.pdf |
Tags: |
Voeg label toe
Geen labels, Wees de eerste die dit record labelt!
|
Gelijkaardige items
-
Optimised Crossover Genetic Algorithms for Combinatorial Optimisation Problems
door: Nazif, Habibeh
Gepubliceerd in: (2010) -
Optimised crossover genetic algorithms for combinatorial optimisation problems /
door: Nazif, Habibeh. -
Genetic algorithms with optimised crossover operator
door: Nazif, Habibeh, et al.
Gepubliceerd in: (2009) -
Optimised crossover genetic algorithm for capacitated vehicle routing problem
door: Nazif, Habibeh, et al.
Gepubliceerd in: (2012) -
Fuzzy genetic algorithms for combinatorial optimisation problems
door: Varnamkhasti, Mohammad Jalali
Gepubliceerd in: (2012)