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ICCS
2004
Springer
13 years 10 months ago
Encoding Multiple Solutions in a Linear Genetic Programming Chromosome
Abstract. Linear Genetic Programming (LGP) is a Genetic Programming variant that uses linear chromosomes for solution encoding. Each LGP chromosome is a sequence of C language inst...
Mihai Oltean, Crina Grosan, Mihaela Oltean
EH
2004
IEEE
107views Hardware» more  EH 2004»
13 years 8 months ago
Evolving Digital Circuits using Multi Expression Programming
Multi Expression Programming (MEP) is a Genetic Programming (GP) variant that uses linear chromosomes for solution encoding. A unique MEP feature is its ability of encoding multipl...
Mihai Oltean, Crina Grosan
ICCS
2004
Springer
13 years 10 months ago
Designing Digital Circuits for the Knapsack Problem
Abstract. Multi Expression Programming (MEP) is a Genetic Programming variant that uses linear chromosomes for solution encoding. A unique feature of MEP is its ability of encoding...
Mihai Oltean, Crina Grosan, Mihaela Oltean
CEC
2007
IEEE
13 years 8 months ago
A multi-layered solution for supporting isp traffic demand using genetic algorithm
This paper proposes a unique feedback governed multi layered architectural model to support ISP's traffic demands with multiple Quality of Service(QoS) constraints. The propos...
Gajaruban Kandavanam, Dmitri Botvich, Sasitharan B...
GECCO
2005
Springer
136views Optimization» more  GECCO 2005»
13 years 10 months ago
Multi-chromosomal genetic programming
This paper introduces an evolutionary algorithm which uses multiple chromosomes to evolve solutions to a symbolic regression problem. Inspiration for this algorithm is provided by...
Rachel Cavill, Stephen L. Smith, Andrew M. Tyrrell