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» Evolving heuristics with genetic programming
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GECCO
2006
Springer
205views Optimization» more  GECCO 2006»
14 years 12 days ago
Alternative evolutionary algorithms for evolving programs: evolution strategies and steady state GP
In contrast with the diverse array of genetic algorithms, the Genetic Programming (GP) paradigm is usually applied in a relatively uniform manner. Heuristics have developed over t...
L. Darrell Whitley, Marc D. Richards, J. Ross Beve...
EPIA
2007
Springer
14 years 2 months ago
A Genetic Programming Approach to the Generation of Hyper-Heuristics for the Uncapacitated Examination Timetabling Problem
Research in the field of examination timetabling has developed in two directions. The first looks at applying various methodologies to induce examination timetables. The second tak...
Nelishia Pillay, Wolfgang Banzhaf
GECCO
2003
Springer
128views Optimization» more  GECCO 2003»
14 years 1 months ago
Evolving Consensus Sequence for Multiple Sequence Alignment with a Genetic Algorithm
In this paper we present an approach that evolves the consensus sequence [25] for multiple sequence alignment (MSA) with genetic algorithm (GA). We have developed an encoding schem...
Conrad Shyu, James A. Foster
AAAI
2010
13 years 10 months ago
Evolving Compiler Heuristics to Manage Communication and Contention
As computer architectures become increasingly complex, hand-tuning compiler heuristics becomes increasingly tedious and time consuming for compiler developers. This paper presents...
Matthew E. Taylor, Katherine E. Coons, Behnam Roba...
CEC
2011
IEEE
12 years 8 months ago
Cost-benefit analysis of using heuristics in ACGP
—Constrained Genetic Programming (CGP) is a method of searching the Genetic Programming search space non-uniformly, giving preferences to certain subspaces according to some heur...
John W. Aleshunas, Cezary Z. Janikow