An Effective Discrete Artificial Bee Colony Algorithm for Scheduling an Automatic-Guided-Vehicle in a Linear Manufacturing Workshop

dc.contributor.author Wenqiang Zou
dc.contributor.author Quanke Pan
dc.contributor.author M. Fatih Tasgetiren
dc.date.accessioned 2025-10-06T17:51:09Z
dc.date.issued 2020
dc.description.abstract This paper deals with a new automatic guided vehicle (AGV) scheduling problem from the material handling process in a linear manufacturing workshop. The problem is to determine a sequence of Cells for AGV to travel to minimize the standard deviation of the waiting time of the Cells and the total travel distance of AGV. For this purpose we first propose an integer linear programming model based on a comprehensive investigation. Then we present an improved nearest-neighbor-based heuristic so as to fast generate a good solution in view of the problem-specific characteristics. Next we propose an effective discrete artificial bee colony algorithm with some novel and advanced techniques including a heuristic-based initialization six neighborhood structures and a new evolution strategy in the onlooker bee phase. Finally the proposed algorithms are empirically evaluated based on several typical instances from the real-world linear manufacturing workshop. A comprehensive and thorough experiment shows that the presented algorithm produces superior results which are also demonstrated to be statistically significant than the existing algorithms. © 2020 Elsevier B.V. All rights reserved.
dc.identifier.doi 10.1109/ACCESS.2020.2973336
dc.identifier.issn 21693536
dc.identifier.issn 2169-3536
dc.identifier.uri https://www.scopus.com/inward/record.uri?eid=2-s2.0-85080860805&doi=10.1109%2FACCESS.2020.2973336&partnerID=40&md5=73a432eda8c3e4696a17a677d8add804
dc.identifier.uri https://gcris.yasar.edu.tr/handle/123456789/9306
dc.language.iso English
dc.publisher Institute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof IEEE Access
dc.source IEEE Access
dc.subject Automated Guided Vehicle, Discrete Artificial Bee Colony Algorithm, Heuristic, Linear Manufacturing Workshop, Scheduling, Evolutionary Algorithms, Integer Programming, Manufacture, Materials Handling, Scheduling, Scheduling Algorithms, Artificial Bee Colony Algorithms, Automated Guided Vehicles, Evolution Strategies, Heuristic, Integer Linear Programming Models, Linear Manufacturing Workshop, Neighborhood Structure, Standard Deviation, Automatic Guided Vehicles
dc.subject Evolutionary algorithms, Integer programming, Manufacture, Materials handling, Scheduling, Scheduling algorithms, Artificial bee colony algorithms, Automated guided vehicles, Evolution strategies, heuristic, Integer linear programming models, linear manufacturing workshop, Neighborhood structure, Standard deviation, Automatic guided vehicles
dc.title An Effective Discrete Artificial Bee Colony Algorithm for Scheduling an Automatic-Guided-Vehicle in a Linear Manufacturing Workshop
dc.type Article
dspace.entity.type Publication
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gdc.coar.type text::journal::journal article
gdc.collaboration.industrial false
gdc.description.endpage 35076
gdc.description.startpage 35063
gdc.description.volume 8
gdc.identifier.openalex W3006151296
gdc.index.type Scopus
gdc.oaire.accesstype GOLD
gdc.oaire.diamondjournal false
gdc.oaire.impulse 17.0
gdc.oaire.influence 3.6901442E-9
gdc.oaire.isgreen true
gdc.oaire.keywords Automated guided vehicle
gdc.oaire.keywords linear manufacturing workshop
gdc.oaire.keywords heuristic
gdc.oaire.keywords discrete artificial bee colony algorithm
gdc.oaire.keywords scheduling
gdc.oaire.keywords Electrical engineering. Electronics. Nuclear engineering
gdc.oaire.keywords TK1-9971
gdc.oaire.popularity 1.4854115E-8
gdc.oaire.publicfunded false
gdc.oaire.sciencefields 0202 electrical engineering, electronic engineering, information engineering
gdc.oaire.sciencefields 02 engineering and technology
gdc.openalex.collaboration International
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gdc.opencitations.count 20
gdc.plumx.crossrefcites 8
gdc.plumx.mendeley 32
gdc.plumx.scopuscites 29
oaire.citation.endPage 35076
oaire.citation.startPage 35063
person.identifier.scopus-author-id Zou- Wenqiang (57216552452), Pan- Quanke (15074237600), Tasgetiren- M. Fatih (6505799356)
project.funder.name This research was partially supported by the National Science Foundation of China 61973203 51575212 and Shanghai Key Laboratory of Power station Automation Technology.
publicationvolume.volumeNumber 8
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