Evolutionary algorithm for package delivery service
Recent years have shown worldwide increasing online shopping activities. Consumers who purchased products online opts for package delivery. This implies an increasing demand for logistic businesses such as warehousing and delivery of goods. Businesses may deliver package to customers via Private Fle...
Saved in:
Main Author: | |
---|---|
Other Authors: | |
Format: | Final Year Project |
Language: | English |
Published: |
2018
|
Subjects: | |
Online Access: | http://hdl.handle.net/10356/73970 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-73970 |
---|---|
record_format |
dspace |
spelling |
sg-ntu-dr.10356-739702023-03-03T20:52:24Z Evolutionary algorithm for package delivery service Wong, Leong Yu Dusit Niyato School of Computer Science and Engineering DRNTU::Engineering::Computer science and engineering Recent years have shown worldwide increasing online shopping activities. Consumers who purchased products online opts for package delivery. This implies an increasing demand for logistic businesses such as warehousing and delivery of goods. Businesses may deliver package to customers via Private Fleet such as trucks and vans, or via common carrier such as Singpost’s speedpost service. This introduces the problem of Vehicle Routing Problem with Private fleet and common Carrier (VRPPC). Determining the optimal route for delivery is vital as the delivery route directly affects the business cost. An optimal delivery route would ensure that all packages are delivered to customers within the customers’ time constraint, and at the minimum cost. There exists many studies done on Vehicle Routing. In this report, the author presents a hybrid genetic algorithm, an evolutionary algorithm, as a viable solution for the VRPPC. The performance of the GA is evaluated using test data from benchmark dataset and from actual Singapore road map. Bachelor of Engineering (Computer Science) 2018-04-23T03:02:13Z 2018-04-23T03:02:13Z 2018 Final Year Project (FYP) http://hdl.handle.net/10356/73970 en Nanyang Technological University 45 p. application/pdf |
institution |
Nanyang Technological University |
building |
NTU Library |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
NTU Library |
collection |
DR-NTU |
language |
English |
topic |
DRNTU::Engineering::Computer science and engineering |
spellingShingle |
DRNTU::Engineering::Computer science and engineering Wong, Leong Yu Evolutionary algorithm for package delivery service |
description |
Recent years have shown worldwide increasing online shopping activities. Consumers who purchased products online opts for package delivery. This implies an increasing demand for logistic businesses such as warehousing and delivery of goods. Businesses may deliver package to customers via Private Fleet such as trucks and vans, or via common carrier such as Singpost’s speedpost service. This introduces the problem of Vehicle Routing Problem with Private fleet and common Carrier (VRPPC). Determining the optimal route for delivery is vital as the delivery route directly affects the business cost. An optimal delivery route would ensure that all packages are delivered to customers within the customers’ time constraint, and at the minimum cost. There exists many studies done on Vehicle Routing. In this report, the author presents a hybrid genetic algorithm, an evolutionary algorithm, as a viable solution for the VRPPC. The performance of the GA is evaluated using test data from benchmark dataset and from actual Singapore road map. |
author2 |
Dusit Niyato |
author_facet |
Dusit Niyato Wong, Leong Yu |
format |
Final Year Project |
author |
Wong, Leong Yu |
author_sort |
Wong, Leong Yu |
title |
Evolutionary algorithm for package delivery service |
title_short |
Evolutionary algorithm for package delivery service |
title_full |
Evolutionary algorithm for package delivery service |
title_fullStr |
Evolutionary algorithm for package delivery service |
title_full_unstemmed |
Evolutionary algorithm for package delivery service |
title_sort |
evolutionary algorithm for package delivery service |
publishDate |
2018 |
url |
http://hdl.handle.net/10356/73970 |
_version_ |
1759856075104845824 |