Please use this identifier to cite or link to this item: https://hdl.handle.net/1959.11/61345
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dc.contributor.authorAbedi, Mehdien
dc.contributor.authorChiong, Raymonden
dc.contributor.authorNoman, Nasimulen
dc.contributor.authorLiao, Xiaoyaen
dc.contributor.authorLi, Debiaoen
dc.date.accessioned2024-07-10T00:58:41Z-
dc.date.available2024-07-10T00:58:41Z-
dc.date.issued2022-
dc.identifier.citationIEEE Transactions on Engineering Management, v.71, p. 4502-4516en
dc.identifier.issn2329-924Xen
dc.identifier.urihttps://hdl.handle.net/1959.11/61345-
dc.description.abstract<p>Batch processing machines, which operate multiple jobs at a time, are commonly used in energy-intensive industries. A significant amount of energy can be saved in such industries using production scheduling as an approach to enhance efficiency. This study deals with an energy-aware scheduling problem for parallel batch processing machines with incompatible families and job release times. In such an environment, a machine may need to wait until all the jobs in the next batch become ready. During waiting time, a machine can be switched off or kept on standby for more energy-efficient scheduling. We first present a mixed-integer linear programming (MILP) model to solve the problem. However, the presented MILP model can only solve small problem instances. We therefore propose an energy-efficient tabu search (ETS) algorithm for solving larger problem instances. The proposed solution framework incorporates multiple neighborhood methods for efficient exploration of the search space. An energy-related heuristic is also integrated into the ETS for minimizing energy consumption during the waiting time. The performance of our proposed ETS algorithm is validated by comparing it with CPLEX for small problem instances and with two other heuristic algorithms for larger problem instances. The contribution of different components in ETS is also established in our experimental studies. The proposed solution framework is expected to bring many benefits in energy-intensive industries both economically and environmentally.</p>en
dc.languageenen
dc.publisherInstitute of Electrical and Electronics Engineersen
dc.relation.ispartofIEEE Transactions on Engineering Managementen
dc.titleA Metaheuristic Framework for Energy-Intensive Industries With Batch Processing Machinesen
dc.typeJournal Articleen
dc.identifier.doi10.1109/TEM.2022.3182380en
local.contributor.firstnameMehdien
local.contributor.firstnameRaymonden
local.contributor.firstnameNasimulen
local.contributor.firstnameXiaoyaen
local.contributor.firstnameDebiaoen
local.profile.schoolSchool of Science & Technologyen
local.profile.emailrchiong@une.edu.auen
local.output.categoryC1en
local.record.placeauen
local.record.institutionUniversity of New Englanden
local.publisher.placeUnited States of Americaen
local.format.startpage4502en
local.format.endpage4516en
local.peerreviewedYesen
local.identifier.volume71en
local.contributor.lastnameAbedien
local.contributor.lastnameChiongen
local.contributor.lastnameNomanen
local.contributor.lastnameLiaoen
local.contributor.lastnameLien
dc.identifier.staffune-id:rchiongen
local.profile.orcid0000-0002-8285-1903en
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.profile.roleauthoren
local.identifier.unepublicationidune:1959.11/61345en
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
dc.identifier.academiclevelAcademicen
local.title.maintitleA Metaheuristic Framework for Energy-Intensive Industries With Batch Processing Machinesen
local.output.categorydescriptionC1 Refereed Article in a Scholarly Journalen
local.search.authorAbedi, Mehdien
local.search.authorChiong, Raymonden
local.search.authorNoman, Nasimulen
local.search.authorLiao, Xiaoyaen
local.search.authorLi, Debiaoen
local.uneassociationNoen
dc.date.presented2022-
local.atsiresearchNoen
local.sensitive.culturalNoen
local.year.published2022en
local.year.presented2022en
local.subject.for20204602 Artificial intelligenceen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.profile.affiliationtypeExternal Affiliationen
local.date.moved2024-07-24en
Appears in Collections:Journal Article
School of Science and Technology
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