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Algorithms 2018,11, 57
andgoal criteria is alsopossible, i.e., the lead timecanbeconsideredas theMScycle time. Hence,
theMSstrategicconfigurationandtacticalplanningcanbeoptimized.
Letusanalysesomeparticular featuresof themodels (1) (seeFigure1).During theconducted
experiments, itwasrevealedthat the followingmodelparameters influencedthe improvementof the
generalquality index:
• the totalnumberofoperationsonaplanninghorizon;
• adispersionofvolumesofoperations;
• aratioof the totalvolumeofoperations to thenumberofprocesses;
• a ratio of the amount of data of operation to the volumeof the operation (relative operation
density).
Onthebasisof theobtainedetalonsolutions,wecanmethodically justify theusageandqualityof
certainheuristics forcertainvariantsof initialdata (seeFigure5).
Figure4.Representationofdynamicchanges inscheduleperformancebyattainablesets.
Figure5.Comparisonofheuristicalgorithms’quality.
159
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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