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Applied mathematics / Mathematics / Operations research / Asymptotic analysis / Mathematical optimization / Big O notation / Theoretical computer science / Computational complexity theory / Analysis of algorithms


Experimental Supplements to the Computational Complexity Analysis of Genetic Programming for Problems Modelling Isolated Program Semantics Tommaso Urli1 , Markus Wagner2 , and Frank Neumann2 1
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Document Date: 2014-09-12 00:58:22

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Company

AMD / HVL / Adelaide SA / /

Facility

University of Adelaide / /

IndustryTerm

population-based multi-objective programming algorithm / singleobjective algorithms / analyzed genetic programming algorithms / multi-objective algorithm / possible solution / evolutionary algorithms / genetic programming algorithms / mutation operator / search space / /

OperatingSystem

Debian GNU/Linux / /

Organization

Italy School of Computer Science / University of Adelaide / Adelaide / /

Person

Xmax / /

Position

stochastic hill-climber / /

ProgrammingLanguage

C / Java / /

Technology

2 multi-objective algorithm / two genetic programming algorithms / population-based multi-objective programming algorithm / 3 Algorithm / singleobjective algorithms / genetic programming algorithms / Java / Linux / GP algorithms / analyzed genetic programming algorithms / /

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