A Single Population Genetic Programming based Ensemble Learning Approach to Job Shop Scheduling
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @InProceedings{Park:2015:GECCOcomp,
-
author = "John Park and Su Nguyen and Mengjie Zhang and
Mark Johnston",
-
title = "A Single Population Genetic Programming based Ensemble
Learning Approach to Job Shop Scheduling",
-
booktitle = "GECCO Companion '15: Proceedings of the Companion
Publication of the 2015 Annual Conference on Genetic
and Evolutionary Computation",
-
year = "2015",
-
editor = "Sara Silva and Anna I Esparcia-Alcazar and
Manuel Lopez-Ibanez and Sanaz Mostaghim and Jon Timmis and
Christine Zarges and Luis Correia and Terence Soule and
Mario Giacobini and Ryan Urbanowicz and
Youhei Akimoto and Tobias Glasmachers and
Francisco {Fernandez de Vega} and Amy Hoover and Pedro Larranaga and
Marta Soto and Carlos Cotta and Francisco B. Pereira and
Julia Handl and Jan Koutnik and Antonio Gaspar-Cunha and
Heike Trautmann and Jean-Baptiste Mouret and
Sebastian Risi and Ernesto Costa and Oliver Schuetze and
Krzysztof Krawiec and Alberto Moraglio and
Julian F. Miller and Pawel Widera and Stefano Cagnoni and
JJ Merelo and Emma Hart and Leonardo Trujillo and
Marouane Kessentini and Gabriela Ochoa and Francisco Chicano and
Carola Doerr",
-
isbn13 = "978-1-4503-3488-4",
-
keywords = "genetic algorithms, genetic programming: Poster",
-
pages = "1451--1452",
-
month = "11-15 " # jul,
-
organisation = "SIGEVO",
-
address = "Madrid, Spain",
-
URL = "http://doi.acm.org/10.1145/2739482.2764651",
-
DOI = "doi:10.1145/2739482.2764651",
-
publisher = "ACM",
-
publisher_address = "New York, NY, USA",
-
abstract = "Genetic Programming based hyper-heuristics (GP-HH) for
dynamic job shop scheduling (JSS) problems are
approaches which aim to address the issue where
heuristics are only effective for specific JSS problem
domains, and that designing effective heuristics for
JSS problems can be difficult. This paper is a
preliminary investigation into improving the robustness
of heuristics evolved by GP-HH by evolving ensembles of
dispatching rules from a single population of GP
individuals. The results show that the current approach
does not evolve significantly better or more robust
rules than a standard GP-HH approach of evolving single
constituent rules.",
-
notes = "Also known as \cite{2764651} Distributed at
GECCO-2015.",
- }
Genetic Programming entries for
John Park
Su Nguyen
Mengjie Zhang
Mark Johnston
Citations