Optimal location queries in road network databases

The Optimal Location Query problem is the exploration for an ideal location that satisfies a specified cost metric in a spatial database. The usage of Optimal Location Query extends to many real life practical scenarios such as scouting a site to open a hypermarket in an area where it would be able...

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Main Author: Lim, Aaron Alexander Qing Rong
Other Authors: Xiao Xiaokui
Format: Final Year Project
Language:English
Published: 2015
Subjects:
Online Access:http://hdl.handle.net/10356/62834
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-628342023-03-03T20:47:11Z Optimal location queries in road network databases Lim, Aaron Alexander Qing Rong Xiao Xiaokui School of Computer Engineering DRNTU::Engineering::Electrical and electronic engineering The Optimal Location Query problem is the exploration for an ideal location that satisfies a specified cost metric in a spatial database. The usage of Optimal Location Query extends to many real life practical scenarios such as scouting a site to open a hypermarket in an area where it would be able attract the most number of customers as possible, yet keeping competition with other retailers at bay. Optimal Location Queries can also be used to facilitate in determining an area where its minimum distance to its benefiters are maximised. The aim of this project would encompass the implementation of Optimal Location Query algorithms presented in the scholarly paper entitled “Optimal Location Queries in Road Networks”. This involves implementing both basic and fine grain partitioning approaches, experimenting and analysing the efficacy on large datasets and producing the result on a graphical user interface. Performance and memory consumption impact was analysed on FGP parameter Θ, number of User-Specified Edges |Ec| / |E|, number of clients |C|, and on Number of Facility |F|. It is noted that FGP performance in computational speed and memory consumption faired better than basic traversal in most test. Also when Θ set at 0.01 (1%) would maximise FGP performance, however, setting Θ at 0.1 can also be considered as it gives a balanced reduction in both computational time and memory. Bachelor of Engineering (Computer Science) 2015-04-29T08:54:51Z 2015-04-29T08:54:51Z 2015 Final Year Project (FYP) http://hdl.handle.net/10356/62834 en Nanyang Technological University 41 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::Electrical and electronic engineering
spellingShingle DRNTU::Engineering::Electrical and electronic engineering
Lim, Aaron Alexander Qing Rong
Optimal location queries in road network databases
description The Optimal Location Query problem is the exploration for an ideal location that satisfies a specified cost metric in a spatial database. The usage of Optimal Location Query extends to many real life practical scenarios such as scouting a site to open a hypermarket in an area where it would be able attract the most number of customers as possible, yet keeping competition with other retailers at bay. Optimal Location Queries can also be used to facilitate in determining an area where its minimum distance to its benefiters are maximised. The aim of this project would encompass the implementation of Optimal Location Query algorithms presented in the scholarly paper entitled “Optimal Location Queries in Road Networks”. This involves implementing both basic and fine grain partitioning approaches, experimenting and analysing the efficacy on large datasets and producing the result on a graphical user interface. Performance and memory consumption impact was analysed on FGP parameter Θ, number of User-Specified Edges |Ec| / |E|, number of clients |C|, and on Number of Facility |F|. It is noted that FGP performance in computational speed and memory consumption faired better than basic traversal in most test. Also when Θ set at 0.01 (1%) would maximise FGP performance, however, setting Θ at 0.1 can also be considered as it gives a balanced reduction in both computational time and memory.
author2 Xiao Xiaokui
author_facet Xiao Xiaokui
Lim, Aaron Alexander Qing Rong
format Final Year Project
author Lim, Aaron Alexander Qing Rong
author_sort Lim, Aaron Alexander Qing Rong
title Optimal location queries in road network databases
title_short Optimal location queries in road network databases
title_full Optimal location queries in road network databases
title_fullStr Optimal location queries in road network databases
title_full_unstemmed Optimal location queries in road network databases
title_sort optimal location queries in road network databases
publishDate 2015
url http://hdl.handle.net/10356/62834
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