Determining the characteristic of difficult job shop scheduling instances for a heuristic solution method

Helga Ingimundardottir, Thomas Philip Runarsson

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Many heuristic methods have been proposed for the job-shop scheduling problem. Different solution methodologies outperform other depending on the particular problem instance under consideration. Therefore, one is interested in knowing how the instances differ in structure and determine when a particular heuristic solution is likely to fail and explore in further detail the causes. In order to achieve this, we seek to characterise features for different difficulties. Preliminary experiments show there are different significant features that distinguish between easy and hard JSSP problem, and that they vary throughout the scheduling process. The insight attained by investigating the relationship between problem structure and heuristic performance can undoubtedly lead to better heuristic design that is tailored to the data distribution under consideration.

Original languageEnglish
Title of host publicationLearning and Intelligent Optimization - 6th International Conference, LION 6, Revised Selected Papers
PublisherSpringer Berlin / Heidelberg
Pages408-412
Number of pages5
ISBN (Print)9783642344121
DOIs
Publication statusPublished - 2012
Event6th International Conference on Learning and Intelligent Optimization, LION 6 - Paris, France
Duration: 16 Jan 201220 Jan 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7219 LNCS

Conference

Conference6th International Conference on Learning and Intelligent Optimization, LION 6
Country/TerritoryFrance
CityParis
Period16/01/1220/01/12

Fingerprint

Dive into the research topics of 'Determining the characteristic of difficult job shop scheduling instances for a heuristic solution method'. Together they form a unique fingerprint.

Cite this