Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

6-2021

Abstract

This research introduces an extension of the Orienteering Problem (OP), known as Set Team Orienteering Problem with Time Windows (STOPTW), in which customers are first grouped into clusters. Each cluster is associated with a profit that will be collected if at least one customer within the cluster is visited. The objective is to find the best route that maximizes the total collected profit without violating time windows and time budget constraints. We propose an adaptive large neighborhood search algorithm to solve newly introduced benchmark instances. The preliminary results show the capability of the proposed algorithm to obtain good solutions within reasonable computational times compared to commercial solver CPLEX.

Keywords

orienteering problem, time windows, adaptive large neighborhood search

Discipline

Artificial Intelligence and Robotics | Operations Research, Systems Engineering and Industrial Engineering | Theory and Algorithms

Research Areas

Intelligent Systems and Optimization

Publication

Learning and Intelligent Optimization: 15th International Conference, LION 15, Athens, Greece, Virtual, June 20-25, 2021: Proceedings

Volume

12931

First Page

142

Last Page

149

ISBN

9783030921200

Identifier

10.1007/978-3-030-92121-7_12

Publisher

Springer

City or Country

Cham

Embargo Period

7-11-2021

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1007/978-3-030-92121-7_12

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