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» Introduction to genetic algorithms
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CEC
2005
IEEE
15 years 3 months ago
Statistical optimisation and tuning of GA factors
This paper presents a practical methodology of improving the efficiency of Genetic Algorithms through tuning the factors significantly affecting GA performance. This methodology is...
Andrei Petrovski, Alexander E. I. Brownlee, John A...
56
Voted
GECCO
1999
Springer
15 years 1 months ago
Use of Preferences for GA-based Multi-objective Optimisation
In this paper we present a method based on preference relations for transforming non–crisp (qualitative) relationships between objectives in multi–objective optimisation into ...
Dragan Cvetkovic, Ian C. Parmee
JCIT
2010
162views more  JCIT 2010»
14 years 4 months ago
Traffic Prediction Based on Improved Neural Network
Artificial neural networks and genetic algorithms derived from the corresponding simulation of biology, anatomy. The paper analyzes the advantages and the disadvantages of the art...
Jian-ming Cui
GECCO
2006
Springer
200views Optimization» more  GECCO 2006»
15 years 1 months ago
A new approach for shortest path routing problem by random key-based GA
In this paper, we propose a Genetic Algorithm (GA) approach using a new paths growth procedure by the random key-based encoding for solving Shortest Path Routing (SPR) problem. An...
Mitsuo Gen, Lin Lin