<p>The purpose of this study is to present an emergency decision making (EDM) technique based on a fuzzy rough set model. In order to build fuzzy rough approximations, researchers in literature use the concept of fuzzy similarity relations. As far as we are aware, there is currently no study approach for fuzzy rough set models based on <InlineEquation ID="IEq6"> <EquationSource Format="TEX">\(\left( \beta ^{\bigstar },\delta ^{\blacklozenge }\right) \)</EquationSource> <EquationSource Format="MATHML"><math> <mfenced close=")" open="("> <msup> <mi>β</mi> <mi>★</mi> </msup> <mo>,</mo> <msup> <mi>δ</mi> <mi>⧫</mi> </msup> </mfenced> </math></EquationSource> </InlineEquation>-fuzzy similarity connections when <InlineEquation ID="IEq7"> <EquationSource Format="TEX">\(\beta ^{\bigstar }\in \left[ 0,0.5\right) ,\)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <msup> <mi>β</mi> <mi>★</mi> </msup> <mo>∈</mo> <mfenced close=")" open="["> <mn>0</mn> <mo>,</mo> <mn>0.5</mn> </mfenced> <mo>,</mo> </mrow> </math></EquationSource> </InlineEquation> and <InlineEquation ID="IEq8"> <EquationSource Format="TEX">\(\delta ^{\blacklozenge }\in \left( 0.5,1\right] \)</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <msup> <mi>δ</mi> <mi>⧫</mi> </msup> <mo>∈</mo> <mfenced close="]" open="("> <mn>0.5</mn> <mo>,</mo> <mn>1</mn> </mfenced> </mrow> </math></EquationSource> </InlineEquation> are involved. This study intends to extend the idea of Pawlak’s rough sets to the so-called <InlineEquation ID="IEq9"> <EquationSource Format="TEX">\(\alpha \)</EquationSource> <EquationSource Format="MATHML"><math> <mi>α</mi> </math></EquationSource> </InlineEquation>-fuzzified multigranulation rough sets based on <InlineEquation ID="IEq10"> <EquationSource Format="TEX">\(\left( \beta ^{\bigstar },\delta ^{\blacklozenge }\right) \)</EquationSource> <EquationSource Format="MATHML"><math> <mfenced close=")" open="("> <msup> <mi>β</mi> <mi>★</mi> </msup> <mo>,</mo> <msup> <mi>δ</mi> <mi>⧫</mi> </msup> </mfenced> </math></EquationSource> </InlineEquation>-fuzzy similarity relations in order to address this research area. Additionally, the approximation created using <InlineEquation ID="IEq11"> <EquationSource Format="TEX">\(\alpha \)</EquationSource> <EquationSource Format="MATHML"><math> <mi>α</mi> </math></EquationSource> </InlineEquation>-fuzzified multigranulation rough sets plays a crucial part in the relationship between <InlineEquation ID="IEq12"> <EquationSource Format="TEX">\(\left( \beta ^{\bigstar },\delta ^{\blacklozenge }\right) \)</EquationSource> <EquationSource Format="MATHML"><math> <mfenced close=")" open="("> <msup> <mi>β</mi> <mi>★</mi> </msup> <mo>,</mo> <msup> <mi>δ</mi> <mi>⧫</mi> </msup> </mfenced> </math></EquationSource> </InlineEquation>-fuzzy similarity relations and crisp set. Moreover, the approximation created on the basis of <InlineEquation ID="IEq13"> <EquationSource Format="TEX">\(\alpha \)</EquationSource> <EquationSource Format="MATHML"><math> <mi>α</mi> </math></EquationSource> </InlineEquation>-fuzzified multigranulation rough sets utilising <InlineEquation ID="IEq14"> <EquationSource Format="TEX">\(\left( \beta ^{\bigstar },\delta ^{\blacklozenge }\right) \)</EquationSource> <EquationSource Format="MATHML"><math> <mfenced close=")" open="("> <msup> <mi>β</mi> <mi>★</mi> </msup> <mo>,</mo> <msup> <mi>δ</mi> <mi>⧫</mi> </msup> </mfenced> </math></EquationSource> </InlineEquation>-fuzzy similarity relations is helpful in understanding various uncertainties and their interrelationships. Also, we explain about the linkages between the novel fuzzy rough approximation operators and the multigranulation <InlineEquation ID="IEq15"> <EquationSource Format="TEX">\(\left( {\mathcal {I}}_{O},O\right) \)</EquationSource> <EquationSource Format="MATHML"><math> <mfenced close=")" open="("> <msub> <mi mathvariant="script">I</mi> <mi>O</mi> </msub> <mo>,</mo> <mi>O</mi> </mfenced> </math></EquationSource> </InlineEquation>-fuzzy rough set model that was constructed using quasi-overlap functions. Then, utilising a multigranulation <InlineEquation ID="IEq16"> <EquationSource Format="TEX">\(\left( {\mathcal {I}}_{O},O\right) \)</EquationSource> <EquationSource Format="MATHML"><math> <mfenced close=")" open="("> <msub> <mi mathvariant="script">I</mi> <mi>O</mi> </msub> <mo>,</mo> <mi>O</mi> </mfenced> </math></EquationSource> </InlineEquation>-fuzzy rough set and <InlineEquation ID="IEq17"> <EquationSource Format="TEX">\(\left( \beta ^{\bigstar },\delta ^{\blacklozenge }\right) \)</EquationSource> <EquationSource Format="MATHML"><math> <mfenced close=")" open="("> <msup> <mi>β</mi> <mi>★</mi> </msup> <mo>,</mo> <msup> <mi>δ</mi> <mi>⧫</mi> </msup> </mfenced> </math></EquationSource> </InlineEquation>-fuzzy similarity relations, we develop three techniques for manipulating unpredictable issues. We also go through how to use the suggested ways to compare them to other current models in order to determine which conditional attribute is best for emergency plans from the ones that are mentioned.</p>