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CEC
2007
IEEE
14 years 4 months ago
Modified genetic algorithm for job-shop scheduling: A gap utilization technique
—The Job-Shop Scheduling Problem (JSSP) is one of the most critical combinatorial optimization problems. The objective of JSSP in this research is to minimize the makespan. In th...
S. M. Kamrul Hasan, Ruhul A. Sarker, David Cornfor...
GECCO
2006
Springer
185views Optimization» more  GECCO 2006»
14 years 2 months ago
Robot gaits evolved by combining genetic algorithms and binary hill climbing
In this paper an evolutionary algorithm is used for evolving gaits in a walking biped robot controller. The focus is fast learning in a real-time environment. An incremental appro...
Lena Mariann Garder, Mats Erling Høvin
GECCO
2007
Springer
192views Optimization» more  GECCO 2007»
14 years 2 months ago
A new crossover technique for Cartesian genetic programming
Genetic Programming was first introduced by Koza using tree representation together with a crossover technique in which random sub-branches of the parents' trees are swapped ...
Janet Clegg, James Alfred Walker, Julian Francis M...
AEI
1999
110views more  AEI 1999»
13 years 10 months ago
Self-tuning fuzzy controller design using genetic optimisation and neural network modelling
This article describes a new adaptive fuzzy logic control scheme. The proposed scheme is based on the structure of the self-tuning regulator and employs neural network and genetic...
Duc Truong Pham, Dervis Karaboga
GECCO
2000
Springer
114views Optimization» more  GECCO 2000»
14 years 2 months ago
Intelligent Recombination Using Individual Learning in a Collective Learning Genetic Algorithm
This paper introduces a new collective learning genetic algorithm (CLGA) which employs individual learning to do intelligent recombination based on a cooperative exchange of knowl...
Terry P. Riopka, Peter Bock