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Algorithms 2018,11, 76
thenstrategiesexceptRandandOPTIwouldhavesufficedwithaprobabilityof1. Figure5bdisplays
results forLigoworkflows. Here, PHEFTandOHEFTwere thebest strategies, followedbyOPTI
andPESS.
Figure 6 shows cpw performance profiles of six strategies forMontage andLigoworkflows
considering τ = [1. . .1.2]. In both cases, PHEFThad the highest probability of being the better
strategyforcpwoptimization. Theprobability that itwasthewinneronagivenproblemwithinfactors
of1.1of thebest solutionwasclose to0.85and1forMontageandLigo, respectively.
(a) (b)
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Figure6. cpwperformanceprofile,τ=[1. . .1.2]. (a)Montage; (b)Ligo.
Figure7showsthemeanperformanceprofilesofallmetrics, scenariosandtest cases, considering
τ=[1. . .1.2]. Therewerediscrepancies inperformancequality. Ifwewant toobtainresultswithin
a factorof1.02of thebest solution, thenPHEFTgeneratedthemwithprobability0.8,whileRandwith
aprobabilityof0.47. Ifwechoseτ=1.2, thenPHEFTproducedresultswithaprobabilityof0.9,and
Randwithaprobabilityof0.76.
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Figure7.Meanperformanceprofileoverallmetricsandtest cases,τ=[1. . .1.2].
7.Conclusions
Effective imageandsignalprocessingworkflowmanagementrequires theefficientallocationof
tasks to limitedresources. In thispaper,wepresentedallocationstrategies that took intoaccountboth
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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