Solving dial-a-ride problem using ant colony optimisation

Dial-a-ride problem refers to the problem of designing scheduled vehicle routes to serve passenger requests in the form of pick-ups and deliveries. It is also called as ‘demand responsive transport’ wherein the customer demands/requests are specified as pick-up and drop-off locations and time window...

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Main Author: Kolumam Anantharamakrishnan Krishnamurthy
Other Authors: Justin Dauwels
Format: Theses and Dissertations
Language:English
Published: 2018
Subjects:
Online Access:http://hdl.handle.net/10356/73136
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-731362023-07-04T15:48:19Z Solving dial-a-ride problem using ant colony optimisation Kolumam Anantharamakrishnan Krishnamurthy Justin Dauwels School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering Dial-a-ride problem refers to the problem of designing scheduled vehicle routes to serve passenger requests in the form of pick-ups and deliveries. It is also called as ‘demand responsive transport’ wherein the customer demands/requests are specified as pick-up and drop-off locations and time windows. In this work, a static multivehicle case of DARP is considered where routes of multiple vehicles are designed to serve customer requests which are known a priori. The DARP necessitates the need of high quality algorithm to provide optimal feasible solutions. The Ant Colony Optimisation intends to achieve this, by leveraging real ant’s intelligence in the decision making process to select the routes efficiently. The work explores an ‘elitist ant’ based ACO algorithm to solve DARP. Additionally, tuning the values of the ant parameters play an important role in improving the solution. The results obtained by using the algorithm perform favourably when compared to existing algorithms. Furthermore, the theoretical results are also validated through simulations carried out in MATLAB. Master of Science (Computer Control and Automation) 2018-01-03T07:26:03Z 2018-01-03T07:26:03Z 2018 Thesis http://hdl.handle.net/10356/73136 en 58 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
Kolumam Anantharamakrishnan Krishnamurthy
Solving dial-a-ride problem using ant colony optimisation
description Dial-a-ride problem refers to the problem of designing scheduled vehicle routes to serve passenger requests in the form of pick-ups and deliveries. It is also called as ‘demand responsive transport’ wherein the customer demands/requests are specified as pick-up and drop-off locations and time windows. In this work, a static multivehicle case of DARP is considered where routes of multiple vehicles are designed to serve customer requests which are known a priori. The DARP necessitates the need of high quality algorithm to provide optimal feasible solutions. The Ant Colony Optimisation intends to achieve this, by leveraging real ant’s intelligence in the decision making process to select the routes efficiently. The work explores an ‘elitist ant’ based ACO algorithm to solve DARP. Additionally, tuning the values of the ant parameters play an important role in improving the solution. The results obtained by using the algorithm perform favourably when compared to existing algorithms. Furthermore, the theoretical results are also validated through simulations carried out in MATLAB.
author2 Justin Dauwels
author_facet Justin Dauwels
Kolumam Anantharamakrishnan Krishnamurthy
format Theses and Dissertations
author Kolumam Anantharamakrishnan Krishnamurthy
author_sort Kolumam Anantharamakrishnan Krishnamurthy
title Solving dial-a-ride problem using ant colony optimisation
title_short Solving dial-a-ride problem using ant colony optimisation
title_full Solving dial-a-ride problem using ant colony optimisation
title_fullStr Solving dial-a-ride problem using ant colony optimisation
title_full_unstemmed Solving dial-a-ride problem using ant colony optimisation
title_sort solving dial-a-ride problem using ant colony optimisation
publishDate 2018
url http://hdl.handle.net/10356/73136
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