# Clustered Orienteering Problem with Subgroups

arXiv: https://arxiv.org/abs/2312.16154 · HTML: https://mlsanity.com/paper/2312.16154/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 21 references that are in the map.
- First posted on arXiv 26 Dec 2023.

## Builds on (most cited first, 2 of 2)

- [A Spatio-Temporal Representation for the Orienteering Problem with Time-Varying Profits](https://mlsanity.com/paper/1611.08037/) (2016)
- [Minimal Exposure Dubins Orienteering Problem](https://mlsanity.com/paper/2010.11932/) (2020)

## Abstract (arXiv)

This paper introduces an extension to the Orienteering Problem (OP), called Clustered Orienteering Problem with Subgroups (COPS). In this variant, nodes are arranged into subgroups, and the subgroups are organized into clusters. A reward is associated with each subgroup and is gained only if all of its nodes are visited; however, at most one subgroup can be visited per cluster. The objective is to maximize the total collected reward while attaining a travel budget. We show that our new formulation has the ability to model and solve two previous well-known variants, the Clustered Orienteering Problem (COP) and the Set Orienteering Problem (SOP), in addition to other scenarios introduced here. An Integer Linear Programming (ILP) formulation and a Tabu Search-based heuristic are proposed to solve the problem. Experimental results indicate that the ILP method can yield optimal solutions at the cost of time, whereas the metaheuristic produces comparable solutions within a more reasonable computational cost.