Solving a multiobjective job shop scheduling problem using Pareto Archived Cuckoo Search

Hanoun, Samer, Creighton, Doug, Nahavandi, Saeid and Kull, Hans 2012, Solving a multiobjective job shop scheduling problem using Pareto Archived Cuckoo Search, in ETFA 2012 : Proceedings of the 2012 17th IEEE International Conference on Emerging Technologies & Factory Automation, IEEE, Piscataway, N.J., pp. 1-8.

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Title Solving a multiobjective job shop scheduling problem using Pareto Archived Cuckoo Search
Author(s) Hanoun, SamerORCID iD for Hanoun, Samer orcid.org/0000-0002-8697-1515
Creighton, DougORCID iD for Creighton, Doug orcid.org/0000-0002-9217-1231
Nahavandi, SaeidORCID iD for Nahavandi, Saeid orcid.org/0000-0002-0360-5270
Kull, Hans
Conference name IEEE Emerging Technologies & Factory Automation. Conference (17th : 2012 : Krakow, Poland)
Conference location Krakow, Poland
Conference dates 17-21 Sep. 2012
Title of proceedings ETFA 2012 : Proceedings of the 2012 17th IEEE International Conference on Emerging Technologies & Factory Automation
Editor(s) [Unknown]
Publication date 2012
Conference series IEEE Emerging Technologies & Factory Automation Conference
Start page 1
End page 8
Total pages 8
Publisher IEEE
Place of publication Piscataway, N.J.
Summary This paper investigates a new approach for solving the multiobjective job shop scheduling problem, namely the Cuckoo Search ( CS) approach. The requirement is to schedule jobs on a single machine so that the total material waste is minimised as well as the total tardiness time. The material waste is quantified in terms of saving factors to show the reduction in material that can be achieved when producing two jobs with the same materials in sequence. The estimated saving factor is used to calculate a cost savings for each job based on its material type. A formulation of multiobjective optimisation problems is adopted to generate the set of schedules that maximise the overall cost savings and minimise the total tardiness time. where all trade-offs are considered for the two conflicting objectives. A Pareto Archived Multiobjective Cuckoo Search (PAMOCS) is developed to find the set ofnondominated Pareto optimal solutions. The solution accuracy of PAMOCS is shown by comparing the closeness of the obtained solutions to the true Pareto front generated by the complete enumeration methad. Results shaw that CS is a very effective and promising technique to solve job shop scheduling problems.
ISBN 9781467347372
Language eng
Field of Research 010303 Optimisation
091099 Manufacturing Engineering not elsewhere classified
Socio Economic Objective 970109 Expanding Knowledge in Engineering
HERDC Research category E1 Full written paper - refereed
Persistent URL http://hdl.handle.net/10536/DRO/DU:30050979

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