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Pareto archived simulated annealing for single machine job shop scheduling with multiple objectives

Hanoun, Samer, Nahavandi, Saeid and Kull, Hans 2011, Pareto archived simulated annealing for single machine job shop scheduling with multiple objectives, in ICCGI 2011 : Sixth International Multi-Conference on Computing in the Global Information Technology, [IARIA], [Luxembourg City, Luxembourg], pp. 99-104.

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Title Pareto archived simulated annealing for single machine job shop scheduling with multiple objectives
Author(s) Hanoun, SamerORCID iD for Hanoun, Samer orcid.org/0000-0002-8697-1515
Nahavandi, SaeidORCID iD for Nahavandi, Saeid orcid.org/0000-0002-0360-5270
Kull, Hans
Conference name International Multi-Conference on Computing in the Global Information Technology (6th : 2011 : Luxembourg City, Luxembourg)
Conference location Luxembourg City, Luxembourg
Conference dates 19-24 June 2011
Title of proceedings ICCGI 2011 : Sixth International Multi-Conference on Computing in the Global Information Technology
Editor(s) Paleologu, Constantin
Mavromoustakis, Constandinos
Minea, Marius
Publication date 2011
Conference series International Multi-Conference on Computing in the Global Information Technology
Start page 99
End page 104
Total pages 6
Publisher [IARIA]
Place of publication [Luxembourg City, Luxembourg]
Keyword(s) multi-criteria optimization
simulated annealing
metaheuristic procedures
pareto optimal
job shop scheduling
Summary In this paper, the single machine job shop scheduling problem is studied with the objectives of minimizing the tardiness and the material cost of jobs. The simultaneous consideration of these objectives is the multi-criteria optimization problem under study. A metaheuristic procedure based on simulated annealing is proposed to find the approximate Pareto optimal (non-dominated) solutions. The two objectives are combined in one composite utility function based on the decision maker’s interest in having a schedule with weighted combination. In view of the unknown nature of the weights for the defined objectives, a priori approach is applied to search for the non-dominated set of solutions based on the Pareto dominance. The obtained solutions set is presented to the decision maker to choose the best solution according to his preferences. The performance of the algorithm is evaluated in terms of the number of non-dominated schedules generated and the proximity of the obtained non-dominated front to the true Pareto front. Results show that the produced solutions do not differ significantly from the optimal solutions.
ISBN 9781612081397
Language eng
Field of Research 010303 Optimisation
Socio Economic Objective 970109 Expanding Knowledge in Engineering
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2011, IARIA
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30042234

Document type: Conference Paper
Collections: Centre for Intelligent Systems Research
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.