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Algorithms 2018,11, 18
IfCondition6 is satisfied, itmeans job i cannotbeprocessedwithinanyoneof themid-peak
periods, let aloneoff-peakperiods. Inotherwords, job i canonlybeused tofill the remaining idle
timeof a certain periodwith lower electricity price. There is an obvious regularity that themore
the remaining idle timeof theoff-peakormid-peakperiod job ioccupy, the lower is itsprocessing
electricitycost. Figure7showsall thepossiblepositions forascenario. Theanalysisprocessof the
possiblepositions that job icanbe inserted into issimilar toCondition4,and, therefore,willnotbe
repeatedhere.
Figure7. IllustrationofCondition6.
Condition7:maxk′∈B{Ik′}=0.
Condition7 implies that all theoff-peakperiods andmid-peakperiods are full, and job i can
onlybe inserted intoon-peakperiods. Ifmaxk′′∈Γ {
Ik′′ }
< ti, job ishouldbe inserted intoallnon-full
on-peak periods bymoving a set of already inserted jobs, and then the positionwith the lowest
insertioncostcanbechosen. Themovementmethodcanrefer toCheetal. [9].
Thecorecomponentoftheheuristicalgorithmisdescribedasapseudocode,showninAlgorithm1.
Note that theargmin(Ik≥ ti)denotes theminimal indexk for Ik≥ ti.
Theorem1.Theproposedheuristic algorithmruns inO(n2m|Γ|) in theworst case.
Proof. Step1runs inO(nlogn) time for sortingnnumbersandStep2requiresO(m) time. Foreach
given job, StepC1 runs inO(|A|) in theworst case andStepC2 requiresO(1). StepsC3 andC5
bothrequireO(|B|)operations in theworst case. StepsC4andC6demandO(nm) to compute the
movementcostwhencalculating the insertioncost. StepC7 includesstepsC7.1andC7.2,wherein
thecomplexityofstepC7.1 isO(|Γ|),andthecomplexityofstepC7.2 isO(nm|Γ|). Therefore, step
C7requiresO(nm|Γ|)operations in theworstcase. Tosummarize, theproposedalgorithmruns in
O(n2m|Γ|) in theworstcase.
Now,assumethatno jobsneedto traverseallnon-fullon-peakperiods, that is, theStepC7.2has
neverbeenused. In this case, the timecomplexityof theproposedalgorithmisO(n2m). However,
theclassicgreedyinsertionalgorithmproposedbyCheetal. [9] requiresO(n2m2)operations in the
worst casewhendealingwith the sameproblem, because their algorithm requires all the jobs to
traverseallnon-fullperiods tofindanoptimumposition.
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Buch Algorithms for Scheduling Problems"
Algorithms for Scheduling Problems
- Titel
- Algorithms for Scheduling Problems
- Autoren
- Frank Werner
- Larysa Burtseva
- Yuri Sotskov
- Herausgeber
- MDPI
- Ort
- Basel
- Datum
- 2018
- Sprache
- englisch
- Lizenz
- CC BY 4.0
- ISBN
- 978-3-03897-120-7
- Abmessungen
- 17.0 x 24.4 cm
- Seiten
- 212
- Schlagwörter
- Scheduling Problems in Logistics, Transport, Timetabling, Sports, Healthcare, Engineering, Energy Management
- Kategorien
- Informatik
- Technik