Fermatean Fuzzy Environment-Based Selection of Firefighting Aircraft Type
by HAVADER Editör Ekibi
The forest fires we see in the news every summer aren't just an environmental disaster — they're also a complex decision-making problem: which aircraft type offers the most effective firefighting capacity, and under what conditions? This study looks for a scientific answer to exactly that question.
Forests cover a third of the world's land area and directly shape ecological balance, biodiversity, and carbon emissions, which is why their protection has become the subject of international agreements from the Rio Convention to the Paris Agreement. Despite this global concern, forest fires remain one of the biggest threats. This study aimed to determine the most suitable firefighting aircraft type should Turkey's General Directorate of Forestry expand its fleet.
The researchers compared three candidate aircraft across 11 evaluation criteria using the SWARA and TOPSIS methods, integrated with Fermatean fuzzy sets derived from three-dimensional fuzzy set extensions. These methods mathematically model decision-makers' uncertain, multi-dimensional preferences — turning seemingly contradictory judgments like "this aircraft is great on speed but weak on cost" into a consistent ranking.
The analysis identified the Beriev Be-200 as the most suitable option. What this finding contributes isn't just an answer to "which aircraft is better" — it's a demonstration that public institutions should make high-cost fleet investment decisions using an objective, multi-dimensional framework rather than intuition or a single criterion like price. An everyday analogy: it's similar to a family buying a car by weighing not just the price, but fuel consumption, maintenance cost, safety rating, and intended use together — except here the decision is a multi-million-dollar public investment with outcomes that can affect lives.
In the end, this study shows that in a world where climate change is expected to increase the frequency of forest fires, the decision of which firefighting aircraft to invest in can now rest on a far more scientific foundation.
Forests cover a third of the world's land area and directly shape ecological balance, biodiversity, and carbon emissions, which is why their protection has become the subject of international agreements from the Rio Convention to the Paris Agreement. Despite this global concern, forest fires remain one of the biggest threats. This study aimed to determine the most suitable firefighting aircraft type should Turkey's General Directorate of Forestry expand its fleet.
The researchers compared three candidate aircraft across 11 evaluation criteria using the SWARA and TOPSIS methods, integrated with Fermatean fuzzy sets derived from three-dimensional fuzzy set extensions. These methods mathematically model decision-makers' uncertain, multi-dimensional preferences — turning seemingly contradictory judgments like "this aircraft is great on speed but weak on cost" into a consistent ranking.
The analysis identified the Beriev Be-200 as the most suitable option. What this finding contributes isn't just an answer to "which aircraft is better" — it's a demonstration that public institutions should make high-cost fleet investment decisions using an objective, multi-dimensional framework rather than intuition or a single criterion like price. An everyday analogy: it's similar to a family buying a car by weighing not just the price, but fuel consumption, maintenance cost, safety rating, and intended use together — except here the decision is a multi-million-dollar public investment with outcomes that can affect lives.
In the end, this study shows that in a world where climate change is expected to increase the frequency of forest fires, the decision of which firefighting aircraft to invest in can now rest on a far more scientific foundation.