Salwani Abdullah
Investigating a Hybrid Metaheuristic For Job Shop Rescheduling
Abdullah, Salwani; Aickelin, Uwe; Burke, Edmund; Din, Aniza; Qu, Rong
Authors
Abstract
Previous research has shown that artificial immune systems can be used to produce robust schedules in a manufacturing environment. The main goal is to develop building blocks (antibodies) of partial schedules that can be used to construct backup solutions (antigens) when disturbances occur during production. The building blocks are created based upon underpinning ideas from artificial immune systems and evolved using a genetic algorithm (Phase I). Each partial schedule (antibody) is assigned a fitness value and the best partial schedules are selected to be converted into complete schedules (antigens). We further investigate whether simulated annealing and the great deluge algorithm can improve the results when hybridised with our artificial immune system (Phase II). We use ten fixed solutions as our target and measure how well we cover these specific scenarios.
Citation
Abdullah, S., Aickelin, U., Burke, E., Din, A., & Qu, R. Investigating a Hybrid Metaheuristic For Job Shop Rescheduling.
Conference Name | Proceedings of the 3rd Australian Conference on Artificial Life (ACAL.07) |
---|---|
Deposit Date | Oct 12, 2007 |
Publicly Available Date | Mar 28, 2024 |
Peer Reviewed | Peer Reviewed |
Public URL | https://nottingham-repository.worktribe.com/output/1017084 |
Files
07acal_aniza.pdf
(163 Kb)
PDF
You might also like
A Method for Evaluating Options for Motif Detection in Electricity Meter Data
(2018)
Journal Article
Using simulation to incorporate dynamic criteria into multiple criteria decision making
(2017)
Journal Article
THCluster: herb supplements categorization for precision traditional Chinese medicine
(2017)
Conference Proceeding
Measuring behavioural change of players in public goods game
(2017)
Book Chapter
Robust datamining
(2017)
Conference Proceeding
Downloadable Citations
About Repository@Nottingham
Administrator e-mail: digital-library-support@nottingham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search