Optimizing the Shortest and Safety Pathways in Infectious Disease Context via the Novel Dhouib‐Matrix‐SPP Method

What is it about?

In this paper, the shortest path problem is considered with emphasis on reducing the COVID-19 contamination risk. Generally, the shortest path problem focuses on planning the minimal path considering the path distance criterion, and here the aim is to generate the shortest safe path with obstacles free collision and virus infection saving. For that, the novel Dhouib-Matrix Shortest Path Problem (DM-SPP) method is enhanced to reduce the probability of catching COVID-19 by keeping people away from crowded and risked space. DM-SPP is enriched with a grid map, namely, the risk pandemic grid map, gathering the human flow density of each area in order to mark the risk epidemic zone. To prove the performance of DM-SPP to optimize the trajectory in COVID-19 virus infection, two case sites are used (a campus case study represented as 40 × 40 grid map and an experimental platform of 50 × 50 grid map). The solutions generated by DM-SPP are graphically represented using the Python programing language, and its results are compared to the results of recently developed metaheuristics in the literature, namely, the classical ant colony optimization metaheuristic, the improved ant colony optimization metaheuristic, the classical A∗ algorithm, and the improved A∗ algorithm.

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Photo by Nick Fewings on Unsplash

Photo by Nick Fewings on Unsplash

Why is it important?

The main contributions and uniqueness of this manuscript include the following five aspects: - The risk pandemic grid map is added to represent the high-density, the medium-density, and the low-density areas in order to effectively prevent and control the epidemic. - The environment and risk pandemic grid maps are combined with different weights to codify each area. - The novel DM-SPP method is enhanced to plan a safe trajectory under the background of COVID-19 using eight movement directions. - A feasible solution with focus on avoiding COVID-19 virus infection is ergonomically generated.

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