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. Attached Files Name Description MIMEType Size Downloads Title Solving a multiobjective job shop scheduling problem using Pareto Archived Cuckoo Search Author(s) Hanoun, Samer orcid.org/0000-0002-8697-1515 Creighton, Doug orcid.org/0000-0002-9217-1231 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 Document type: Conference Paper Collections: Institute for Intelligent Systems Research and Innovation (IISRI) GTP Research   Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Versions Version Filter Type Tue, 05 Mar 2013, 14:55:48 EST Wed, 05 Jun 2013, 15:34:37 EST Wed, 05 Jun 2013, 15:46:45 EST Wed, 05 Jun 2013, 15:48:17 EST Wed, 12 Jun 2013, 10:06:54 EST Thu, 15 May 2014, 09:55:33 EST Wed, 02 Jul 2014, 16:01:03 EST Wed, 21 Oct 2015, 14:41:09 EST Wed, 21 Oct 2015, 18:02:01 EST Filtered Full Citation counts:   Cited 3 times in TR Web of Science Cited 23 times in Scopus Search Google Scholar Access Statistics: 723 Abstract Views, 6 File Downloads  -  Detailed Statistics Created: Tue, 05 Mar 2013, 14:55:48 EST

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