Version 1

Benchmark instances for the stochastic hybrid truck-drone routing problem

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rashid, reza

Description

To evaluate the performance of the proposed model in figure 1, we generated 180 small-sized instances and 180 medium-sized instances, and 60 large-sized instances. We generated customer locations in a 1000*1000m2 square. Then randomly assigned to three customer classes. As the second-class and the third-class customers must be covered with the rendezvous locations, we created them in a way that at least one rendezvous node is in sight radius of each second-class or third-class customer. The sight radius is considered to be 100 meters for this data generation. We have defined two locations for the depot as follows: the vertex of the square (0,0) and the center of the square (500,500). We assumed 10 meters per second for truck speed and 20 meters per second for drone speed. In this way, we created 36 various instance types and generated 10 instances for each type.

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Mentions (0)

Metrics

Dataset Index

1.6

FAIR Score

73%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

4TU.ResearchData

Assigned Domain

Subfield

Industrial and Manufacturing Engineering

Field

Engineering

Domain

Physical Sciences

Confidence Score

46%

Source

Scholar Data Model

Keywords

Transportation and Freight ServicesFOS: Economics and businessApplied MathematicsFOS: Mathematicslast mile deliveryTruck and drone routing problemdrone delivery;mixed integer programming (MIP);Vehicle Routing Problem (VRP)

Normalization Factors

FT

15.38

CTw

1.00

MTw

1.00