Iterated local search algorithm for the capacitated team orienteering problem

This paper focuses on a recent variant of the Orienteering Problem (OP), namely the Capacitated Team Orienteering Problem (CTOP). In this problem, each node is associated with a demand that needs to be satisfied and a score that need to be collected. Given a set of homogeneous fleet of vehicles, the...

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Main Authors: GUNAWAN, Aldy, NG, Kien Ming, YU, Vincent F., ADIPRASETYO, Gordy, LAU, Hoong Chuin
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Language:English
Published: Institutional Knowledge at Singapore Management University 2018
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Online Access:https://ink.library.smu.edu.sg/sis_research/4373
https://ink.library.smu.edu.sg/context/sis_research/article/5376/viewcontent/CTOP.pdf
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spelling sg-smu-ink.sis_research-53762019-06-13T09:50:11Z Iterated local search algorithm for the capacitated team orienteering problem GUNAWAN, Aldy NG, Kien Ming YU, Vincent F. ADIPRASETYO, Gordy LAU, Hoong Chuin This paper focuses on a recent variant of the Orienteering Problem (OP), namely the Capacitated Team Orienteering Problem (CTOP). In this problem, each node is associated with a demand that needs to be satisfied and a score that need to be collected. Given a set of homogeneous fleet of vehicles, the main objective is to find a path for each available vehicle in order to maximize the total score, without violating the capacity and time budget of each vehicle. We propose an Iterated Local Search algorithm that has been applied in solving various variants of the OP. We propose two ILS algorithms with the main difference lies on the implementation of local search operators. For solving small instances, we implement two different strategies, either accepting a new solution as long as it improves the quality of the solutions or accepting a new solution as long as there is no constraint violation. For solving large instances, we simplify the move operator of local search in order to reduce the computational time. Instead of exploring all possible nodes in all paths to be moved, we only focus on nodes in the path with the least remaining amount of time. Computational experiments on benchmark data sets illustrate the efficiency and effectiveness of the proposed approach. 2018-08-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/4373 https://ink.library.smu.edu.sg/context/sis_research/article/5376/viewcontent/CTOP.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Orienteering problem Iterated local search Capacitated orienteering problem Operations Research, Systems Engineering and Industrial Engineering Theory and Algorithms
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Orienteering problem
Iterated local search
Capacitated orienteering problem
Operations Research, Systems Engineering and Industrial Engineering
Theory and Algorithms
spellingShingle Orienteering problem
Iterated local search
Capacitated orienteering problem
Operations Research, Systems Engineering and Industrial Engineering
Theory and Algorithms
GUNAWAN, Aldy
NG, Kien Ming
YU, Vincent F.
ADIPRASETYO, Gordy
LAU, Hoong Chuin
Iterated local search algorithm for the capacitated team orienteering problem
description This paper focuses on a recent variant of the Orienteering Problem (OP), namely the Capacitated Team Orienteering Problem (CTOP). In this problem, each node is associated with a demand that needs to be satisfied and a score that need to be collected. Given a set of homogeneous fleet of vehicles, the main objective is to find a path for each available vehicle in order to maximize the total score, without violating the capacity and time budget of each vehicle. We propose an Iterated Local Search algorithm that has been applied in solving various variants of the OP. We propose two ILS algorithms with the main difference lies on the implementation of local search operators. For solving small instances, we implement two different strategies, either accepting a new solution as long as it improves the quality of the solutions or accepting a new solution as long as there is no constraint violation. For solving large instances, we simplify the move operator of local search in order to reduce the computational time. Instead of exploring all possible nodes in all paths to be moved, we only focus on nodes in the path with the least remaining amount of time. Computational experiments on benchmark data sets illustrate the efficiency and effectiveness of the proposed approach.
format text
author GUNAWAN, Aldy
NG, Kien Ming
YU, Vincent F.
ADIPRASETYO, Gordy
LAU, Hoong Chuin
author_facet GUNAWAN, Aldy
NG, Kien Ming
YU, Vincent F.
ADIPRASETYO, Gordy
LAU, Hoong Chuin
author_sort GUNAWAN, Aldy
title Iterated local search algorithm for the capacitated team orienteering problem
title_short Iterated local search algorithm for the capacitated team orienteering problem
title_full Iterated local search algorithm for the capacitated team orienteering problem
title_fullStr Iterated local search algorithm for the capacitated team orienteering problem
title_full_unstemmed Iterated local search algorithm for the capacitated team orienteering problem
title_sort iterated local search algorithm for the capacitated team orienteering problem
publisher Institutional Knowledge at Singapore Management University
publishDate 2018
url https://ink.library.smu.edu.sg/sis_research/4373
https://ink.library.smu.edu.sg/context/sis_research/article/5376/viewcontent/CTOP.pdf
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