The University of Southampton
University of Southampton Institutional Repository

A semi-automated design of instance-based fuzzy parameter tuning for metaheuristics based on decision tree induction

A semi-automated design of instance-based fuzzy parameter tuning for metaheuristics based on decision tree induction
A semi-automated design of instance-based fuzzy parameter tuning for metaheuristics based on decision tree induction
Two main concepts are established in the literature for the Parameter Setting Problem (PSP) of metaheuristics: Parameter Tuning Strategies (PTS) and Parameter Control Strategies (PCS). While PTS result in a fixed parameter setting for a set of problem instances, PCS are incorporated into the metaheuristic and adapt parameter values according to instance-specific performance feedback. The idea of Instance-specific Parameter Tuning Strategies (IPTS) is aiming to combine advantages of both tuning and control strategies by enabling the adoption of parameter values tailored to instance-specific characteristics a priori to running the metaheuristic. This requires, however, a significant knowledge about the impact of
instance-characteristics on heuristic performance. This paper presents an approach that semi-automatically designs the fuzzy logic rule base to obtain instance-specific parameter values by means of decision trees. This enables the user to automate the process of converting insights about instance-specific information and its impact on heuristic performance into a fuzzy rule base IPTS system. The system incorporates the decision maker's preference about the trade-off between computational time and solution quality
0160-5682
782-793
Ries, Jana
463ef2f9-566f-4175-b39c-b2eeb0f5b04a
Beullens, Patrick
893ad2e2-0617-47d6-910b-3d5f81964a9c
Ries, Jana
463ef2f9-566f-4175-b39c-b2eeb0f5b04a
Beullens, Patrick
893ad2e2-0617-47d6-910b-3d5f81964a9c

Ries, Jana and Beullens, Patrick (2015) A semi-automated design of instance-based fuzzy parameter tuning for metaheuristics based on decision tree induction. Journal of the Operational Research Society, 66, 782-793. (doi:10.1057/jors.2014.46).

Record type: Article

Abstract

Two main concepts are established in the literature for the Parameter Setting Problem (PSP) of metaheuristics: Parameter Tuning Strategies (PTS) and Parameter Control Strategies (PCS). While PTS result in a fixed parameter setting for a set of problem instances, PCS are incorporated into the metaheuristic and adapt parameter values according to instance-specific performance feedback. The idea of Instance-specific Parameter Tuning Strategies (IPTS) is aiming to combine advantages of both tuning and control strategies by enabling the adoption of parameter values tailored to instance-specific characteristics a priori to running the metaheuristic. This requires, however, a significant knowledge about the impact of
instance-characteristics on heuristic performance. This paper presents an approach that semi-automatically designs the fuzzy logic rule base to obtain instance-specific parameter values by means of decision trees. This enables the user to automate the process of converting insights about instance-specific information and its impact on heuristic performance into a fuzzy rule base IPTS system. The system incorporates the decision maker's preference about the trade-off between computational time and solution quality

Text
__soton.ac.uk_UDE_PersonalFiles_Users_pb2n10_mydocuments_PB Work_My papers_Jana JORS_Semi-automated Fuzzy IPTS - Ries Beullens.pdf - Other
Download (403kB)

More information

Published date: 15 May 2015
Organisations: Operational Research

Identifiers

Local EPrints ID: 363756
URI: http://eprints.soton.ac.uk/id/eprint/363756
ISSN: 0160-5682
PURE UUID: c01c66ad-3821-4dbe-827a-7f07de8c2bc6
ORCID for Patrick Beullens: ORCID iD orcid.org/0000-0001-6156-3550

Catalogue record

Date deposited: 03 Apr 2014 09:29
Last modified: 15 Mar 2024 03:32

Export record

Altmetrics

Contributors

Author: Jana Ries

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×