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Figure4. Single-PointCrossover
5. EvaluationExperiment
5.1. ExperimentalEnvironment
Table1. InitialResources
Generation Time(s) Money(yen) Stamina
low 500 15000 7500 1000
medium 500 30000 15000 2000
high 500 60000 30000 4000
Wehaveimplementedouralgorithm inPython3andexecutedtheimplementedalgorithm
on aPCwith Intel Core i7-8550U1.8GHz, 16GBRAMandWindows 10HomeOS.
Further,weexecutedouralgorithm for threedifferent initial resourceassignmentsshown
in Table 1, to investigate the correlations between the derived solutions and the initial
resources. In this experiment,we derived the information on the resource consumption
onmoneyand time for eachpath (solution) byusingGoogleMapAPI. Since it is difïŹ-
cult toknowactual staminaconsumptionandsatisfactiongotonapath,weset the imag-
inaryvalues empirically.Modelingof stamina consumption and satisfaction acquisition
(proposed in [15]) isour futurework.
In this experiment, we targeted 30 PoIs in Higashiyama-area of Kyoto, Japan as
showninFig.11, andwedetermined thestart and thegoalpoints inadvance.Moreover,
becauseof the shortdistancebetweenPoIs,weusedcar (taxi), busandwalkingas types
of transportation.
5.2. Relationshipbetween InitialResourceandSolutions
Fig. 5 shows the scattered plot of initial solutions generated at random (at 0-thGener-
ation). These solutions are paths consisting of 10 randomly selectedPoIs including the
start and goal points. Furthermore, Fig. 6, Fig. 7 andFig. 8 plot 100 solutions that our
algorithm calculated at 500-th generationwith low,medium and high initial resources.
Table2 showsapart of thederived solutions, andvalues represent consumed/remaining
resources and satisfaction value. This result supports that our proposed algorithm can
derive diverse solutions considering the trade-offs between resources and satisfaction
values.
MoreoverFigs. 6â8 indicate relationships betweenmoney, time, stamina and satis-
faction.SpeciïŹcally, inFig. 6, solutions aredense in the left-bottom area, because solu-
tions are limitedby low initial resources in this case.On theother hand,medium initial
resource case (Fig. 7), solutions aremore distributed inwider area than the low initial
Y.Hiranoetal. /AMethod
forGeneratingMultipleTourRoutes186
Intelligent Environments 2019
Workshop Proceedings of the 15th International Conference on Intelligent Environments
- Title
- Intelligent Environments 2019
- Subtitle
- Workshop Proceedings of the 15th International Conference on Intelligent Environments
- Authors
- Andrés Muñoz
- Sofia Ouhbi
- Wolfgang Minker
- Loubna Echabbi
- Miguel Navarro-CĂa
- Publisher
- IOS Press BV
- Date
- 2019
- Language
- German
- License
- CC BY-NC 4.0
- ISBN
- 978-1-61499-983-6
- Size
- 16.0 x 24.0 cm
- Pages
- 416
- Category
- TagungsbÀnde