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.
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Acknowledgment
This research was partially supported by the Ministry of Science and Technology of Taiwan under grant MOST 108-2221-E-011-051-MY3 and the Center for Cyber-Physical System Innovation from The Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan.
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Gunawan, A., Yu, V.F., Sutanto, A.N., Jodiawan, P. (2021). Set Team Orienteering Problem with Time Windows. In: Simos, D.E., Pardalos, P.M., Kotsireas, I.S. (eds) Learning and Intelligent Optimization. LION 2021. Lecture Notes in Computer Science(), vol 12931. Springer, Cham. https://doi.org/10.1007/978-3-030-92121-7_12
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DOI: https://doi.org/10.1007/978-3-030-92121-7_12
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