Evidence map›Paper›PMID 36855677›Full record

ArticleJournal of global optimization : an international journal dealing with theoretical and computational aspects of seeking global optima and their applications in science, management and engineering2023

A three-stage stochastic optimization model integrating 5G technology and UAVs for disaster management.

Gabriella Colajanni, Patrizia Daniele, Anna Nagurney, Ladimer S Nagurney, Daniele Sciacca

Abstract read
In one paragraph

Article in Journal of global optimization : an international journal dealing with theoretical and computational aspects of seeking global optima and their applications in science, management and engineering, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Gabriella ColajanniDepartment of Mathematics and Computer Science, University of Catania, Viale Andrea Doria, 6, 95125 Catania, Italy.ORCID 0000-0002-8183-241X
Patrizia DanieleDepartment of Mathematics and Computer Science, University of Catania, Viale Andrea Doria, 6, 95125 Catania, Italy.
Anna NagurneyDepartment of Operations and Information Management, Isenberg School of Management, University of Massachusetts, Amherst, MA 01003 USA.
Ladimer S NagurneyDepartment of Electrical and Computer Engineering, University of Hartford, West Hartford, CT 06117 USA.
Daniele SciaccaDepartment of Mathematics and Computer Science, University of Catania, Viale Andrea Doria, 6, 95125 Catania, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this paper, we develop a three-stage stochastic network-based optimization model for the provision of 5G services with Unmanned Aerial Vehicles (UAVs) in the disaster management phases of: preparedness, response and recover/reconstruction. Users or devices on the ground request services of a fleet of controller UAVs in flight and the requested services are executed by a fleet of UAVs organized as a Flying Ad-Hoc Network and interconnected via 5G technology. A disaster scenario can create difficulties for the provision of services by service providers. For this reason, in the first stage, service providers make predictions about possible scenarios in the second stage. Therefore, the first stage represents the preparedness phase, the second stage represents the response phase, followed by the recovery/reconstruction phase, represented by the third stage. In each of the three stages, service providers seek to maximize the amount of services to be performed, assigning each service a priority. They also aim to, simultaneously, minimize the total management costs of requests, the transmission and execution costs of services, the costs to increase the resources of the pre-existing network and, if need be, to reduce them in the recovery/reconstruction phase. For the proposed multi-stage stochastic optimization model, we provide variational formulations for which we investigate the existence and uniqueness of the solution. Finally, a detailed numerical example is solved in order underline some of the key aspects of the model. This paper adds to the literature on the rigorous mathematical modeling of advanced technologies for disaster management.

Indexed as

5GDisaster managementNetwork modelStochastic optimizationUAVs

Identifiers

PMID36855677
PMCPMC9950713

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.