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Algorithms 2018,11, 50
Fromtheconceptualpointofview, thispaperdealswithamixed integernon-linear (MINLP)
schedulingproblem[5]that isrelaxedtoacombinatorialsetof linearprogrammingproblemsduetothe
linear“makespan”objective function.Asabasicapproachwetakethedisjunctivemodel [4].Asimilar
approachwasdemonstrated in [7]where the authors deployed the concept of parallel dedicated
machines scheduling subject to precedence constraints and implemented aheuristic algorithm to
generateasolution.
2.MaterialsandMethods
Inorder to formalize thecontinuous-timeschedulingproblemwewillneedto introduceseveral
basicdefinitionsandvariables.After that,wewill formasystemofconstraints that reflectdifferent
physical, logical and economic restrictions that are in place for real industrial processes. Finally,
introducingtheobjective functionwillfinishtheformulationofRCPSPasanoptimizationproblem
suitable forsolving.
2.1.NotionsandBaseData forScheduling
Stickingto the industrial schedulingalsoknownas the JobShopproblem, letusdefinethemain
notions thatwewilluse in the formulation:
• Theenterprise functioningprocessutilizes resourcesofdifferent types (for instancemachines,
personnel, riggings, etc.). The set of the resources is indicated by a variable R = {Rr},
r=1,. . . , |R|.
• Themanufacturingprocedureof theenterprise is formalizedasasetofoperations J tiedwith
eachotherviaprecedencerelations. Precedencerelationsarebrought toamatrixG=< gij>,
i= 1,. . . , |J|, j= 1,. . . , |J|. Eachelementof thematrix gij = 1 iff theoperation j follows the
operation iandzerootherwisegij=0.
• Eachoperation i isdescribedbydurationτi. Elementsτi, i=1,. . . , |J|, formavectorofoperations’
durations−→τ.
• Each operation i has a list of resources it uses while running. Necessity for resources for
each operation is represented by thematrixOp =< opir >, i = 1,. . . , |J|, r = 1,. . . , |R|.
Eachelementof thematrixopir=1 iff theoperation iof themanufacturingprocessallocates the
resource r. Allothercasesbringtheelement tozerovalueopir=0.
• The inputordersof theenterpriseareconsideredasmanufacturingtasks for thecertainamount
ofendproductandareorganized intoasetF. Eachorder is characterizedby theendproduct
amount vf and thedeadline df , f = 1,. . . , |F|. Elements inside F are sorted in thedeadline
ascendingorder.
Using thedefinitions introducedabove,wecannowformalize theschedulingprocessas residing
all |J|operationsofall |F|ordersonthesetof resourcesR.Mathematically thismeansdefiningthe
start timeofeachoperation i=1,. . . , |J|ofeachorder f=1,. . . , |F|.
2.2. Continuous-TimeProblemSetting
Thecontinuous-timecase is formulatedaroundthevariables that standfor thestartmomentsof
eachoperation iofeachorder f: xif ≥0, i=1,. . . , |J|, f=1,. . . , |F| [3]. Thevariablesxif ≥0can
becombinedinto |F|vectors−→xf ≥0. Themainconstraintsof theoptimizationprobleminthatcaseare:
• Precedencegraphof themanufacturingprocedure:
G−→xf ≥ (−→xf +−→τ ), f=1,. . . , |F|.
• Meetingdeadlines forallorders
x|J|f+τ|J| ≤ df , f=1,. . . , |F|.
116
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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