Novel Applications of the Team Orienteering Problem in Health Care Logistics

Aringhieri, Roberto; Bigharaz, Sara; Duma, Davide; Guastalla, Alberto

doi:10.1007/978-3-030-95380-5_21

Cited by 4 publications

(2 citation statements)

References 18 publications

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“…Fundamentally, OP involves finding a single route to maximize total rewards by visiting a subset of vertices on a graph, adhering to a path-length limit. Practically, OP has wide applications ranging from planning optimal sightseeing tours in tourism (Gavalas et al 2015) to enhancing delivery routes in supply chain logistics (Aringhieri et al 2022).…”

Section: Related Workmentioning

confidence: 99%

“…This paper considers a generalized version of OP, namely Time-varying Reward OP (TR-OP), where the reward at each vertex is a known function that changes over time. TR-OP arises in applications such as logistics (Aringhieri et al 2022), surveillance (Yu, Schwager, and Rus 2016), and transportation system (Martins et al 2021). Consider an example (Fig.…”

Section: Introductionmentioning

confidence: 99%

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Heuristic Search for the Orienteering Problem with Time-Varying Reward

Cao,

Xu,

Zhang

et al. 2024

SOCS

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The Orienteering Problem (OP) seeks a path on a graph to maximize total rewards collected subject to a path length budget. Typically, a reward is achieved by visiting a vertex in the graph, and such a reward is constant for all time. This paper considers a variant of OP where the reward of each vertex is an arbitrary time-dependent function, and hence the name time-varying reward OP (TR-OP). To solve this problem, we develop a novel heuristic search algorithm called Reward Maximization A* (RMA*), which is guaranteed to find an optimal solution to TR-OP. We also develop a fast method to compute an admissible heuristic for RMA* that can effectively direct the search to save computational effort. Furthermore, we introduce a hyper-parameter in RMA* that trades off between solution quality and runtime efficiency for RMA*. We benchmark RMA* against a recent dynamic programming (DP) approach, which runs fast in practice, but has no guarantee of the solution optimality. In our tests, RMA* reduces the runtime by up to 70% compared to DP. By adjusting the hyper-parameter, RMA* is able to find solutions with up to 30% more rewards than those found by DP.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Heuristic Search for the Orienteering Problem with Time-Varying Reward

Cao,

Xu,

Zhang

et al. 2024

SOCS

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An enhanced heuristic for the team orienteering problem with time windows considering multiple deliverymen

Huang²

2022

Soft Comput

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Fairness in ambulance routing for post disaster management

Aringhieri

Bigharaz

Duma

et al. 2021

Cent Eur J Oper Res

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Disaster management generally includes the post-disaster stage, which consists of the actions taken in response to the disaster damages. These actions include the employment of emergency plans and assigned resources to (i) rescue affected people immediately, (ii) deliver personnel, medical care and equipment to the disaster area, and (iii) aid to prevent the infrastructural and environmental losses. In the response phase, humanitarian logistics directly influence the efficiency of the relief operation. Ambulances routing problem is defined as employing the optimisation tools to manage the flow of ambulances for finding the best ambulance tours to transport the injured to hospitals. Researchers pointed out the importance of equity and fairness in humanitarian relief services: managing the operations of ambulances in the immediate aftermath of a disaster must be done impartially and efficiently to rescue affected people with different priority in accordance with the restrictions. Our research aim is to find the best ambulance tours to transport the patients during a disaster in relief operations while considering fairness and equity to deliver services to patients in balance. The problem is formulated as a new variant of the team orienteering problem with hierarchical objectives to address also the efficiency issue. Due to the limitation of solving the proposed model using a general-purpose solver, we propose a new hybrid algorithm based on a machine learning and neighbourhood search. Based on a new set of realistic benchmark instances, our quantitative analysis proves that our algorithm is capable to largely reduce the solution running time especially when the complexity of the problem increases. Further, a comparison between the fair solution and the system optimum solution is also provided.

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Novel Applications of the Team Orienteering Problem in Health Care Logistics

Cited by 4 publications

References 18 publications

Heuristic Search for the Orienteering Problem with Time-Varying Reward

Heuristic Search for the Orienteering Problem with Time-Varying Reward

An enhanced heuristic for the team orienteering problem with time windows considering multiple deliverymen

Fairness in ambulance routing for post disaster management

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