Integrated Algorithm for Multi-Criteria Group Decision-Making in Evacuation Tasks

This article presents an integrated algorithm for multicriteria group decision-making based on an intuitionistic fuzzy hybrid averaging operator for selecting the optimal evacuation strategy. The algorithm is multilevel, where the first level involves constructing a task model in the form of an evacuation transportation network. At the second level, the ranking of evacuation spaces is performed to determine their optimal order based on various criteria, such as room capacity, ease of evacuation, safety level of the room as a shelter, time required to organize evacuation from the location, and distance from the source of danger. The ranking of evacuation spaces is carried out using multicriteria group decision-making and an intuitionistic fuzzy hybrid averaging operator to model the doubts and uncertainties of experts in evaluating evacuation criteria, alternatives, and expert importance. The algorithm operates with linguistic expert assessments, allowing for the calculation of expert and criterion weights based on these assessments for effective decision-making. Aggregation of assessments is performed using a modified algorithm that allows for the operation of criterion weights represented as intuitionistic fuzzy values, unlike traditional crisp numbers, based on developed modified operators for raising fuzzy numbers to a fuzzy power to account for the doubts and uncertainties of the expert group. At the third level, macroscopic dynamic flow evacuation is carried out, considering the possibility of accommodating evacuees in spaces that are not shelters. The advantage of the proposed algorithm is its ability to model the transportation of evacuees under dynamic conditions from hazardous areas, taking into account their placement in intermediate points to maximize the number of lives saved, considering the uncertainty of the environment, the fuzzy nature of factors influencing evacuation decisions, and the uncertainties and doubts of the expert group in evaluating evacuation strategies. To confirm the effectiveness of the developed algorithm, evacuation modeling was conducted, and a software environment was created, implemented in JavaScript. A comparison of the developed decision-making algorithm based on the IFHA operator, operating with fuzzy weights of criteria, with existing algorithms was carried out, and a conclusion was made about the reliability of the proposed algorithm. An assessment of the dependence of the algorithm’s runtime on the input size was conducted, confirming the possibility of using the proposed algorithm for large buildings and transportation networks.

Publication Details

Journal
Informatics and Automation
Published
2025-10-08
DOI
https://doi.org/10.15622/ia.24.5.2
Citations
3
Primary Topic
Pregnancy and preeclampsia studies
Type
article
Field-Weighted Citation Impact
6.17

Funders

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article

Integrated Algorithm for Multi-Criteria Group Decision-Making in Evacuation Tasks

3 citations
Informatics and Automation
Pregnancy and preeclampsia studies
6.17
article

Integrated Algorithm for Multi-Criteria Group Decision-Making in Evacuation Tasks

article en
3 citations

Abstract

This article presents an integrated algorithm for multicriteria group decision-making based on an intuitionistic fuzzy hybrid averaging operator for selecting the optimal evacuation strategy. The algorithm is multilevel, where the first level involves constructing a task model in the form of an evacuation transportation network. At the second level, the ranking of evacuation spaces is performed to determine their optimal order based on various criteria, such as room capacity, ease of evacuation, safety level of the room as a shelter, time required to organize evacuation from the location, and distance from the source of danger. The ranking of evacuation spaces is carried out using multicriteria group decision-making and an intuitionistic fuzzy hybrid averaging operator to model the doubts and uncertainties of experts in evaluating evacuation criteria, alternatives, and expert importance. The algorithm operates with linguistic expert assessments, allowing for the calculation of expert and criterion weights based on these assessments for effective decision-making. Aggregation of assessments is performed using a modified algorithm that allows for the operation of criterion weights represented as intuitionistic fuzzy values, unlike traditional crisp numbers, based on developed modified operators for raising fuzzy numbers to a fuzzy power to account for the doubts and uncertainties of the expert group. At the third level, macroscopic dynamic flow evacuation is carried out, considering the possibility of accommodating evacuees in spaces that are not shelters. The advantage of the proposed algorithm is its ability to model the transportation of evacuees under dynamic conditions from hazardous areas, taking into account their placement in intermediate points to maximize the number of lives saved, considering the uncertainty of the environment, the fuzzy nature of factors influencing evacuation decisions, and the uncertainties and doubts of the expert group in evaluating evacuation strategies. To confirm the effectiveness of the developed algorithm, evacuation modeling was conducted, and a software environment was created, implemented in JavaScript. A comparison of the developed decision-making algorithm based on the IFHA operator, operating with fuzzy weights of criteria, with existing algorithms was carried out, and a conclusion was made about the reliability of the proposed algorithm. An assessment of the dependence of the algorithm’s runtime on the input size was conducted, confirming the possibility of using the proposed algorithm for large buildings and transportation networks.

Informatics and AutomationVol. 24(5)
Russian Science Foundation, Southern Federal University
Peace, Justice and strong institutions
Openalex Percentile: Top 3%
Pregnancy and preeclampsia studies
6.17
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