arXiv subjects

Alberto Guastalla

Publications and source records attributed to Alberto Guastalla.

3 recordsLinked to original sources

arXiv2026

The Stochastic Team Orienteering Problem

This paper analyses the Stochastic Team Orienteering Problem (STOP), a stochastic variant of the Team Orienteering Problem (TOP). In the STOP, travel times are represented by random variables. The objective is to determine a set of routes that maximises the expected collected profit. We model the problem as a two-stage stochastic integer program and propose an exact solution method based on the Integer L-shaped method. We also consider a set of non-linear chance constraints to restrict the search to highly reliable routes. In the first-stage, a set of routes is selected, while in the second-stage the recourse evaluates the expected profit of the selected routes. We present a new set of optimality cuts and strengthen the formulation by considering valid inequalities and constraints liftings. Computational results provide a comprehensive analysis of the algorithm using the standard TOP benchmark dataset from the literature.

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arXiv2025

Heuristic approaches for a new variant of the Team Orienteering Problem

In this paper we tackle the Team Orienteering Problem with Service Times, Mandatory Nodes and Incompatibilities, introduced in~\cite{Guastalla2024} and arising from two real-world healthcare applications. We propose two heuristic algorithms in the form of a Variable Descent Neighbourhood algorithm and a matheuristic based on a Cuts Separation approach. For the former, we also provide a multi-thread version exploiting its intrinsic capability to be parallelised. Both algorithms include a specific heuristic routine to provide a starting feasible solution, since finding a feasible solution has been proved to be NP-complete. The results of our heuristic algorithms are compared with an exact cutting plane approach and have complementary strengths and weaknesses. They are also evaluated on existing TOP benchmarks against TOP state-of-the-art algorithms, demonstrating their competitiveness on general grounds.

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arXiv2024

The Team Orienteering Problem with Service Times and Mandatory & Incompatible Nodes

The Team Orienteering Problem with Service Times and Mandatory & Incompatible Nodes (TOP-ST-MIN) is a variant of the classic Team Orienteering Problem (TOP), which includes three novel features that stem from two real-world problems previously studied by the authors. We prove that even finding a feasible solution is NP-complete. Two versions of this variant are considered in our study. For such versions, we proposed two alternative mathematical formulations, a mixed and a compact formulations. Based on the compact formulation, we developed a Cutting-Plane Algorithm (CPA) exploiting five families of valid inequalities. Extensive computational experiments showed that the CPA outperforms CPLEX in solving the new benchmark instances, generated in such a way to evaluate the impact of the three novel features that characterise the problem. The CPA is also competitive for the TOP since it is able to solve almost the same number of instances as the state-of-art algorithms.

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