On the Synthesis of Perturbative Heuristics for Multiple Combinatorial Optimisation Domains
Created by W.Langdon from
gp-bibliography.bib Revision:1.7970
- @InProceedings{DBLP:conf/ppsn/StoneHP18,
-
author = "Christopher Stone and Emma Hart and Ben Paechter",
-
title = "On the Synthesis of Perturbative Heuristics for
Multiple Combinatorial Optimisation Domains",
-
booktitle = "Parallel Problem Solving from Nature - {PPSN} {XV} -
15th International Conference, Part {I}",
-
year = "2018",
-
editor = "Anne Auger and Carlos M. Fonseca and Nuno Lourenco and
Penousal Machado and Luis Paquete and
L. Darrell Whitley",
-
volume = "11101",
-
series = "Lecture Notes in Computer Science",
-
pages = "170--182",
-
address = "Coimbra, Portugal",
-
month = sep # " 8-12",
-
publisher = "Springer",
-
keywords = "genetic algorithms, genetic programming, Grammatical
Evolution, PonyGE2, TSPLIB",
-
DOI = "doi:10.1007/978-3-319-99253-2_14",
-
timestamp = "Tue, 11 Feb 2020 11:20:56 +0100",
-
biburl = "https://dblp.org/rec/conf/ppsn/StoneHP18.bib",
-
bibsource = "dblp computer science bibliography, https://dblp.org",
-
abstract = "Hyper-heuristic frameworks, although intended to be
cross-domain at the highest level, rely on a set of
domain-specific low-level heuristics at lower levels.
For some domains, there is a lack of available
heuristics, while for novel problems, no heuristics
might exist. We address this issue by introducing a
novel method, applicable in multiple domains, that
constructs new low-level heuristics for a domain. The
method uses grammatical evolution to construct iterated
local search heuristics: it can be considered
cross-domain in that the same grammar can evolve
heuristics in multiple domains without requiring any
modification, assuming that solutions are represented
in the same form. We evaluate the method using
benchmarks from the traveling-salesman (TSP) and
multi-dimensional knapsack (MKP) domain. Comparison to
existing methods demonstrates that the approach
generates low-level heuristics that outperform
heuristic methods for TSP and are competitive for
MKP.",
- }
Genetic Programming entries for
Christopher Stone
Emma Hart
Ben Paechter
Citations