Time dependent orienteering problem with time windows and service time dependent profits

This paper addresses the time dependent orienteering problem with time windows and service time dependent profits (TDOPTW-STP). In the TDOPTW-STP, each vertex is assigned a minimum and a maximum service time and the profit collected at each vertex increases linearly with the service time. The goal i...

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Main Authors: Khodadadian, M., Divsalar, A., Verbeeck, C., GUNAWAN, Aldy, Vansteenwegen, P.
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Language:English
Published: Institutional Knowledge at Singapore Management University 2022
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Online Access:https://ink.library.smu.edu.sg/sis_research/7091
https://ink.library.smu.edu.sg/context/sis_research/article/8094/viewcontent/Time_OP_TW_av.pdf
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spelling sg-smu-ink.sis_research-80942022-04-07T07:34:37Z Time dependent orienteering problem with time windows and service time dependent profits Khodadadian, M. Divsalar, A. Verbeeck, C. GUNAWAN, Aldy Vansteenwegen, P. This paper addresses the time dependent orienteering problem with time windows and service time dependent profits (TDOPTW-STP). In the TDOPTW-STP, each vertex is assigned a minimum and a maximum service time and the profit collected at each vertex increases linearly with the service time. The goal is to maximize the total collected profit by determining a subset of vertices to be visited and assigning appropriate service time to each vertex, considering a given time budget and time windows. Moreover, travel times are dependent of the departure times. To solve this problem, a mixed integer linear model is formulated and a metaheuristic algorithm based on variable neighborhood search (VNS) is developed. This algorithm uses three specifically designed neighborhood structures able to deal with the variable service times and profits of vertices. Extensive computational experiments are conducted on test instances adapted from the TDOPTW benchmarks, to validate the performance of our solution approach. Furthermore, a real instance for the city of Shiraz (Iran) is generated. Experimental results demonstrate the suitability of the TDOPTW-STP in practice, and demonstrate that the proposed algorithm is able to obtain high-quality solutions in real-time. Sensitivity analyses clearly show the significant impact of the service time dependent profits on the route plan, especially in the presence of travel time dependency and time windows. 2022-07-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/7091 info:doi/10.1016/j.cor.2022.105794 https://ink.library.smu.edu.sg/context/sis_research/article/8094/viewcontent/Time_OP_TW_av.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 Real data set Service time dependent profits Time dependent orienteering problem Tourist trip planning Variable neighborhood search Computer Sciences Operations Research, Systems Engineering and Industrial Engineering Transportation
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Real data set
Service time dependent profits
Time dependent orienteering problem
Tourist trip planning
Variable neighborhood search
Computer Sciences
Operations Research, Systems Engineering and Industrial Engineering
Transportation
spellingShingle Real data set
Service time dependent profits
Time dependent orienteering problem
Tourist trip planning
Variable neighborhood search
Computer Sciences
Operations Research, Systems Engineering and Industrial Engineering
Transportation
Khodadadian, M.
Divsalar, A.
Verbeeck, C.
GUNAWAN, Aldy
Vansteenwegen, P.
Time dependent orienteering problem with time windows and service time dependent profits
description This paper addresses the time dependent orienteering problem with time windows and service time dependent profits (TDOPTW-STP). In the TDOPTW-STP, each vertex is assigned a minimum and a maximum service time and the profit collected at each vertex increases linearly with the service time. The goal is to maximize the total collected profit by determining a subset of vertices to be visited and assigning appropriate service time to each vertex, considering a given time budget and time windows. Moreover, travel times are dependent of the departure times. To solve this problem, a mixed integer linear model is formulated and a metaheuristic algorithm based on variable neighborhood search (VNS) is developed. This algorithm uses three specifically designed neighborhood structures able to deal with the variable service times and profits of vertices. Extensive computational experiments are conducted on test instances adapted from the TDOPTW benchmarks, to validate the performance of our solution approach. Furthermore, a real instance for the city of Shiraz (Iran) is generated. Experimental results demonstrate the suitability of the TDOPTW-STP in practice, and demonstrate that the proposed algorithm is able to obtain high-quality solutions in real-time. Sensitivity analyses clearly show the significant impact of the service time dependent profits on the route plan, especially in the presence of travel time dependency and time windows.
format text
author Khodadadian, M.
Divsalar, A.
Verbeeck, C.
GUNAWAN, Aldy
Vansteenwegen, P.
author_facet Khodadadian, M.
Divsalar, A.
Verbeeck, C.
GUNAWAN, Aldy
Vansteenwegen, P.
author_sort Khodadadian, M.
title Time dependent orienteering problem with time windows and service time dependent profits
title_short Time dependent orienteering problem with time windows and service time dependent profits
title_full Time dependent orienteering problem with time windows and service time dependent profits
title_fullStr Time dependent orienteering problem with time windows and service time dependent profits
title_full_unstemmed Time dependent orienteering problem with time windows and service time dependent profits
title_sort time dependent orienteering problem with time windows and service time dependent profits
publisher Institutional Knowledge at Singapore Management University
publishDate 2022
url https://ink.library.smu.edu.sg/sis_research/7091
https://ink.library.smu.edu.sg/context/sis_research/article/8094/viewcontent/Time_OP_TW_av.pdf
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