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Algorithms 2018,11, 43
For22 instances,no integersolutionwasfoundor themodelprovidedasolutionwithzerovalue. In
mostcases, theheuristic solutionsweremuchbetter thanthe lowerboundgivenbyCPLEX, leadingto
verynegativeRPD,ascanbeobservedinTable11.
Table11.Overallperformance (averageRPD)ofheuristics inrelation to lowerboundgivenbyCPLEX
bynumberof jobs for instancesofGroup2.
n H1 H2 H3 H4 H5 H6 H7 H8 H9 H10
15 6.5 1.0 10.3 6.9 1.0 1.0 56.7 41.1 28.2 36.8
20 −5.0 −6.5 4.0 −2.8 −8.8 −8.8 66.5 49.6 23.1 41.1
30 −49.0 −52.5 −38.0 −40.1 −52.0 −52.0 68.4 57.2 −7.4 38.5
80 −1080.2 −1082.0 −1001.7 −1032.6 −1082.0 −1082.0 −13.5 −93.2 −764.4 −251.9
100 −1276.7 −1276.7 −990.8 −1159.3 −1276.7 −1276.7 −460.6 −518.8 −865.0 −276.1
Themorenegative is theRPDofaheuristic, thebetter is its result inrelationto the lowerbound.
It couldbenotedthateventheworstheuristic (H7)providedresults thatwerebetter thanthe lower
boundgivenbyCPLEX.Theseresultsconfirmallprevious inferences. Thecoincidenceof theresults
forH5andH6isremarkable, suggestingthatneighborhoodsearchesdonot improvethesolutionof
mediumandlarge instances.
5.4. ComputationalEfficiency
Thecomparisonofcomputationalefficiency, i.e., theaverageconsumptionofCPUtimemeasured
inmilliseconds(ms),ofeachheuristic forGroups1and2, theenumerationmethodandCPLEXfor
Group1areshowninTable12.
Table12.Computationalefficiency(averageCPUtimes inmilliseconds).
SolutionMethod Group1 Group2
H1 0.08 67.99
H2 0.33 7895.49
H3 0.03 72.55
H4 0.32 7820.17
H5 0.01 1.21
H6 0.13 391.51
H7 0.01 1.28
H8 0.12 190.49
H9 0.06 79.02
H10 0.05 56.29
EM 1483.65 –
Model 199,882.99 –
Asexpected, theEMandCPLEXconsumedmuchmoreCPUtimethantheheuristics. For the
small instances (Group1), thecomputational timesofall theheuristicswerealmostzeroand, for the
mediumandlargeones (Group2),H2andH4tookthe longest times,nearly8sonaverage,which
wererelativelyhighcomparedwith thoseofothermethodsbutdoesnotprecludetheiruse.Allother
heuristics requiredfar less timethanonesecondwhichdemonstratedtheviabilityofusingthemin
practice. It isworthnoting thatH5,whichrankedsecondwithasolutionqualityveryclose to that
ofH6, consumed less thanahalf secondonaverage for large instances, thereby indicating itshigh
computationalefficiency.
Finally, inanoverallanalysisof theresultsandthesolutionapproachesproposedinthispaper
(exactandheuristic), theapplicabilityof thedevelopedheuristicswere justifiedanddemonstrated
in terms of both solution quality (an average of 0.6%deviation from the optimumwith the best
heuristicH6)andcomputationalefficiency(anaverageof0.4s for large instancesalsowithH6). The
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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