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KBSE
1997
IEEE
13 years 12 months ago
Genetic Algorithms for Dynamic Test Data Generation
In software testing, it is often desirable to find test inputs that exercise specific program features. To find these inputs by hand is extremely time-consuming, especially whe...
Christoph C. Michael, Gary McGraw, Michael Schatz,...
GECCO
1999
Springer
116views Optimization» more  GECCO 1999»
14 years 11 hour ago
Dynamic Degree Constrained Network Design: A Genetic Algorithm Approach
The design and development of network infrastructure to support mission-critical operations has become a critical and complicated issue. In this study we explore the use of geneti...
Chao-Hsien Chu, G. Premkumar, Carey Chou, Jianzhon...
GECCO
2006
Springer
159views Optimization» more  GECCO 2006»
13 years 11 months ago
A genetic model based on simulated crossover of quaternary genes for quadratic fitness
We present a genetic model based on simulated recombination of fixed sequences of quaternary genes (assuming four distinct forms, or alleles). States and dynamics of the infinite ...
Marco Carpentieri, Vito Fedullo
KES
1999
Springer
14 years 1 hour ago
Dynamic Demes parallel genetic algorithm
Abstract—Dynamic Demes is a new method for the parallelisation of evolutionary algorithms. It was derived as a combination of two other parallelisation algorithms: the master-sla...
Mariusz Nowostawski, Riccardo Poli
AAAI
1998
13 years 9 months ago
Optimal 2D Model Matching Using a Messy Genetic Algorithm
A Messy Genetic Algorithm is customized toflnd'optimal many-to-many matches for 2D line segment models. The Messy GA is a variant upon the Standard Genetic Algorithm in which...
J. Ross Beveridge