Riccardo Poli, William B. Langdon, Nicholas F. McPhee: A Field Guide to Genetic Programming: Lulu. com, 2008, 250 pp, ISBN 978-1-4092-0073-4
M O'Neill - 2009 - Springer
The latest book on Genetic Programming, Poli, Langdon and McPhee's (with contributions
from John R. Koza) A Field Guide to Genetic Programming represents an exciting landmark …
from John R. Koza) A Field Guide to Genetic Programming represents an exciting landmark …
Automatically finding patches using genetic programming
Automatic program repair has been a longstanding goal in software engineering, yet
debugging remains a largely manual process. We introduce a fully automated method for …
debugging remains a largely manual process. We introduce a fully automated method for …
A review of tournament selection in genetic programming
Y Fang, J Li - International symposium on intelligence computation …, 2010 - Springer
This paper provides a detailed review of tournament selection in genetic programming. It
starts from introducing tournament selection and genetic programming, followed by a brief …
starts from introducing tournament selection and genetic programming, followed by a brief …
Multitask multiobjective genetic programming for automated scheduling heuristic learning in dynamic flexible job-shop scheduling
Evolutionary multitask multiobjective learning has been widely used for handling more than
one multiobjective task simultaneously. However, it is rarely used in dynamic combinatorial …
one multiobjective task simultaneously. However, it is rarely used in dynamic combinatorial …
A survey of semantic methods in genetic programming
Several methods to incorporate semantic awareness in genetic programming have been
proposed in the last few years. These methods cover fundamental parts of the evolutionary …
proposed in the last few years. These methods cover fundamental parts of the evolutionary …
Open issues in genetic programming
It is approximately 50 years since the first computational experiments were conducted in
what has become known today as the field of Genetic Programming (GP), twenty years since …
what has become known today as the field of Genetic Programming (GP), twenty years since …
An efficient genetic programming approach to design priority rules for resource-constrained project scheduling problem
In recent years, machine learning techniques, especially genetic programming (GP), have
been a powerful approach for automated design of the priority rule-heuristics for the …
been a powerful approach for automated design of the priority rule-heuristics for the …
On using surrogates with genetic programming
One way to accelerate evolutionary algorithms with expensive fitness evaluations is to
combine them with surrogate models. Surrogate models are efficiently computable …
combine them with surrogate models. Surrogate models are efficiently computable …
Hyper-heuristic evolution of dispatching rules: A comparison of rule representations
Dispatching rules are frequently used for real-time, online scheduling in complex
manufacturing systems. Design of such rules is usually done by experts in a time consuming …
manufacturing systems. Design of such rules is usually done by experts in a time consuming …
Why is optimization difficult?
This chapter aims to address some of the fundamental issues that are often encountered in
optimization problems, making them difficult to solve. These issues include premature …
optimization problems, making them difficult to solve. These issues include premature …