Designing a new sustainable healthcare network considering the COVID-19 pandemic: Artificial intelligence-based solutions

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F25%3A10256545" target="_blank" >RIV/61989100:27510/25:10256545 - isvavai.cz</a>

Result on the web

<a href="https://www.sciencedirect.com/science/article/pii/S0957417424022243?via%3Dihub#ak005" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0957417424022243?via%3Dihub#ak005</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.eswa.2024.125357" target="_blank" >10.1016/j.eswa.2024.125357</a>

Result language

angličtina

Original language name

Designing a new sustainable healthcare network considering the COVID-19 pandemic: Artificial intelligence-based solutions

Original language description

The COVID-19 pandemic, which is still spreading its new mutations all around the world, is considered a healthcare challenge around the world. The best approach to forestall this pandemic is to avoid exposure to the virus. Therefore, medical protective equipment is essential for fighting this pandemic. This underlines the chief role of having a sustainable supply chain network (SCN) for producing and distributing personal protective equipment to avoid shortage and augmenting costs. The reality, however, is that the COVID-19 pandemic leads to many developments in countries and this study is another step for these purposes. This research develops a multi-period, multi-objective, multi-echelon, and multi-product medical protective equipment sustainable SCN considering the production, distribution, allocation, and inventory with “risk pooling” strategy effect with the aim of filling the existing gaps in health SCN research during the COVID-19 pandemic. By applying the risk pooling strategy, lower inventory levels or higher service levels can be achieved without increasing inventory costs. This model explores the possibility of lateral transshipments between distribution centers, as a way to increase the reliability of SCN performance. We model a new production, inventory, distribution, location, and allocation problem and consider four objectives for our suggested model (i) minimizing total SCN costs, (ii) minimizing environmental effects, (iii) minimizing social impacts, and (iv) maximizing the reliability of demand delivery. The proposed model simultaneously examines all three dimensions of sustainability (economic, environmental, and social) as well as the reliability of demand delivery. Considering all of these decisions and assumptions brings the studied problem closer to reality. We employ various algorithms for solving our developed model with different sizes: the improved version of the augmented ε-constraint (AUGMECON2) algorithm for small and medium-sized problems and two meta-heuristic algorithms, i.e., Multi-Objective Whale Optimization Algorithm (MOWOA) and Multi-Objective Variable Neighborhood Search (MOVNS) algorithm, for large-sized ones. The Taguchi approach is used to tune the parameters of meta-heuristic algorithms, and a comparison is performed using four evaluation metrics: Mean Ideal Distance (MID), Number of Pareto Solutions (NPS), Maximum Spread (MS), and Spread of Non-Dominance Solution (SNS). Proposed solving methods for the studied problem and making comparisons between them are another innovation of this study. A couple of numerical examples are provided to illustrate the applicability of the presented solution methods. Finally, sensitivity analysis for problem parameters is performed to validate our suggested model. Our study reveals the superiority of the MOWOA over the other algorithms.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

50200 - Economics and Business

Project

—

Continuities

O - Projekt operacniho programu

Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Expert Systems with Applications

ISSN

0957-4174

e-ISSN

1873-6793

Volume of the periodical

260

Issue of the periodical within the volume

January

Country of publishing house

GB - UNITED KINGDOM

Number of pages

26

Pages from-to

125357

UT code for WoS article

001368269700001

EID of the result in the Scopus database

2-s2.0-85205228996