dc.contributor.authorGanguly, Srinjoy
dc.contributor.authorChowdhury, Arkabandhu
dc.contributor.authorMukherjee, Swahum
dc.contributor.authorSuganthan, P. N.
dc.contributor.authorDas, Swagatam
dc.contributor.authorChua, Tay Jin
dc.date.accessioned2013-12-16T03:53:35Z
dc.date.available2013-12-16T03:53:35Z
dc.date.copyright2013en_US
dc.date.issued2013
dc.identifier.citationGanguly S., Chowdhury A., Mukherjee S., Suganthan P.N., Das S., & Chua T.J. (2013). A Hybrid Discrete Differential Evolution Algorithm for Economic Lot Scheduling Problem with Time Variant Lot Sizing. 7th International Conference, SOCO’12, 188, 1-12.en_US
dc.identifier.urihttp://hdl.handle.net/10220/18248
dc.description.abstractThis article presents an efficient Hybrid Discrete Differential Evolution (HDDE) model to solve the Economic Lot Scheduling Problem (ELSP) using a time variant lot sizing approach. This proposed method introduces a novel Greedy Reordering Local Search (GRLS) operator as well as a novel Discrete DE scheme for solving the problem. The economic lot-scheduling problem (ELSP) is an important production scheduling problem that has been intensively studied. In this problem, several products compete for the use of a single machine, which is very similar to the real-life industrial scenario, in particular in the field of remanufacturing. The experimental results indicate that the proposed algorithm outperforms several previously used heuristic algorithms under the time-varying lot sizing approach.en_US
dc.language.isoenen_US
dc.titleA hybrid discrete differential evolution algorithm for economic lot scheduling problem with time variant lot sizingen_US
dc.typeConference Paper
dc.contributor.conferenceInternational Conference on Soft Computing Models in Industrial and Environmental Applications (7th : 2012 : Ostrava, Czech)en_US
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen_US
dc.contributor.organizationA*STAR SIMTechen_US
dc.identifier.urlhttp://link.springer.com.ezlibproxy1.ntu.edu.sg/chapter/10.1007%2F978-3-642-32922-7_1#


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