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Article
EvaluatingTypicalAlgorithmsofCombinatorial
OptimizationtoSolveContinuous-TimeBased
SchedulingProblem
AlexanderA.Lazarev*, IvanNekrasov*,† andNikolayPravdivets †
InstituteofControlSciences,65ProfsoyuznayaStreet, 117997Moscow,Russia;pravdivets@ya.ru
* Correspondence: jobmath@mail.ru (A.A.L.); ivannekr@mail.ru (I.N.);Tel.: +7-495-334-87-51 (A.A.L.)
† Theseauthorscontributedequally to thiswork.
Received: 22February2018;Accepted: 12April2018;Published: 17April2018
Abstract: Weconsider one approach to formalize theResource-ConstrainedProject Scheduling
Problem(RCPSP) in termsofcombinatorialoptimizationtheory. Thetransformationof theoriginal
problemintocombinatorialsettingisbasedoninterpretingeachoperationasanatomicentitythathas
adefineddurationandhas toberesidedonthecontinuous timeaxismeetingadditional restrictions.
Thesimplestcaseofcontinuous-timeschedulingassumesone-to-onecorrespondenceofresourcesand
operationsandcorrespondsto the linearprogrammingproblemsetting.However, real scheduling
problemsincludemany-to-onerelationswhich leads to theadditionalcombinatorial component in
the formulationduetooperationscompetition.Weresearchhowtoapplyseveral typicalalgorithms
tosolve theresultedcombinatorialoptimizationproblem: enumeration includingbranch-and-bound
method,gradientalgorithm,randomsearchtechnique.
Keywords:RCPSP;combinatorialoptimization; scheduling; linearprogramming;MES; JobShop
1. Introduction
TheResource-ConstrainedProjectSchedulingProblem(RCPSP)hasmanypracticalapplications.
Oneof themostobviousanddirectapplicationsofRCPSPisplanningthe fulfilmentofplannedorders
at themanufacturingenterprise [1] that isalsosometimesnamedJobShop. TheJobShopscheduling
process traditionally resides inside theManufacturingExecutionSystemsscope [2] andbelongs to
principlebasicmanagement tasksofanyindustrialenterprise.Historically the JobShopscheduling
problemhas twoformalmathematicalapproaches [3]: continuousanddiscrete timeproblemsettings.
In thispaper,weresearchthecontinuous-timeproblemsetting,analyze itsbottlenecks,andevaluate
effectivenessofseveral typicalalgorithmstofindanoptimalsolution.
Thecontinuous-timeJobShopschedulingapproachhasbeenextensivelyresearchedandapplied
indifferent industrial spheres throughout thepast50years.Oneof themostpopularclassicalproblem
settingswasformulated in[4]byManneasadisjunctivemodel. Thisproblemsettingformsabasic
systemofrestrictionsevaluatedbydifferentcomputationalalgorithmsdependingontheparticular
practical featuresof themodelused.Awideoverviewofdifferentcomputationalapproaches to the
schedulingproblemisconducted in [5,6]. Thearticle [5] considers69papersdatingback to theXX
century, revealingthe followingmaintrends in JobShopscheduling:
- Enumeratingtechniques
- Differentkindsof relaxation
- Artificial intelligence techniques (neuralnetworks,geneticalgorithms,agents, etc.)
Artificial intelligence (AI) techniqueshavebecomemainstreamnowadays. Thepaper [6]givesa
detailed listofAI techniquesandmethodsusedforscheduling.
Algorithms 2018,11, 50;doi:10.3390/a11040050 www.mdpi.com/journal/algorithms115
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book Algorithms for Scheduling Problems"
Algorithms for Scheduling Problems
- Title
- Algorithms for Scheduling Problems
- Authors
- Frank Werner
- Larysa Burtseva
- Yuri Sotskov
- Editor
- MDPI
- Location
- Basel
- Date
- 2018
- Language
- English
- License
- CC BY 4.0
- ISBN
- 978-3-03897-120-7
- Size
- 17.0 x 24.4 cm
- Pages
- 212
- Keywords
- Scheduling Problems in Logistics, Transport, Timetabling, Sports, Healthcare, Engineering, Energy Management
- Categories
- Informatik
- Technik