Novel Pythagorean fuzzy score function to optimize fuzzy transportation models

Uncertainty in transportation models arises from several factors, including fluctuating demand, variable supply, transportation costs and unpredictable external conditions like market changes or delays. Traditional optimization methods struggle to account for this variability, as they rely on precis...

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Main Authors: Ritu, Tarun Kumar, Jahnvi, Kapil Kumar, Nitesh Dhiman, M.K. Sharma
Format: Article
Language:English
Published: Elsevier 2025-03-01
Series:Results in Engineering
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Online Access:http://www.sciencedirect.com/science/article/pii/S2590123025001367
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author Ritu
Tarun Kumar
Jahnvi
Kapil Kumar
Nitesh Dhiman
M.K. Sharma
author_facet Ritu
Tarun Kumar
Jahnvi
Kapil Kumar
Nitesh Dhiman
M.K. Sharma
author_sort Ritu
collection DOAJ
description Uncertainty in transportation models arises from several factors, including fluctuating demand, variable supply, transportation costs and unpredictable external conditions like market changes or delays. Traditional optimization methods struggle to account for this variability, as they rely on precise inputs. To address the inherent uncertainty in classical transportation problems, fuzzy logic and its extensions such as intuitionistic fuzzy set (IFS), interval valued intuitionistic fuzzy set (IVIFS), Pythagorean fuzzy set (PFS) etc. are employed in the existing literature. This paper utilizes an advanced extension of fuzzy sets, known as Interval-Valued Pythagorean Fuzzy Sets (IVPFS) in transportation models. IVPFS provides a more flexible framework by allowing the MD & NMD to be interval values to capture a wider range of uncertainty. This paper introduces a novel score function dealing with IVPFS to enhance the decision-making processes in uncertain environments. As compare to the other score function of IVPFS, the proposed score function provide us more optimal results. which is also helpful to evaluate more optimal cost of PFTP. Also, the proposed score function integrates these interval values to quantify and rank the alternatives more effectively.However, a notable trade-off is the increased computational complexity due to the use of interval values in the membership and non-membership functions, particularly in larger-scale transportation problems. Furthermore, the different models (Type-1, Type-2 and Type-3) show varied effectiveness in different scenarios: Type-1 performs best when cost uncertainty is primary, Type-2 is suitable when both supply and demand are uncertain and Type-3 addresses all three factors-supply, demand and cost-under uncertainty.Three types of interval valued Pythagorean fuzzy transportation problems (IVPFTP) are examined in this study: Type-1 considers cost in a Pythagorean fuzzy nature, Type-2 addresses both supply and demand in a Pythagorean fuzzy nature and Type-3 incorporates supply, demand and cost all are in a Pythagorean fuzzy nature. Through comprehensive numerical analysis, In Type-1 IVPFTP the cost dropped from 5.19 to 0.675, for Type-2 IVPFTP cost dropped from 0.2615 to 0.001869 and for Type-3 IVPFTP cost dropped from0.17435 to 0.0013879.Thereafter, it was observed that the proposed score function provides a more optimal transportation cost.Also, our findings demonstrate the significant cost reductions and improved decision-making capabilities across different types of IVPFTP models to highlight the efficiency of the proposed score function in handling uncertainty within the transportation problems.
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spelling doaj-art-808a23037b9f4da58168b3763047e8562025-01-27T04:22:09ZengElsevierResults in Engineering2590-12302025-03-0125104048Novel Pythagorean fuzzy score function to optimize fuzzy transportation models Ritu0Tarun Kumar1 Jahnvi2Kapil Kumar3Nitesh Dhiman4M.K. Sharma5Department of Mathematics, Chaudhary Charan Singh University, Meerut, India, 250004Department of Mathematics, Chaudhary Charan Singh University, Meerut, India, 250004Department of Mathematics, Chaudhary Charan Singh University, Meerut, India, 250004Department of Mathematics, Chaudhary Charan Singh University, Meerut, India, 250004; Department of Mathematics, Atma Ram Sanatan Dharma College (University of Delhi), New Delhi, 110021, IndiaDepartment of Mathematics, Zakir Husain Delhi College, New Delhi, India, 110002Department of Mathematics, Chaudhary Charan Singh University, Meerut, India, 250004; Corresponding author.Uncertainty in transportation models arises from several factors, including fluctuating demand, variable supply, transportation costs and unpredictable external conditions like market changes or delays. Traditional optimization methods struggle to account for this variability, as they rely on precise inputs. To address the inherent uncertainty in classical transportation problems, fuzzy logic and its extensions such as intuitionistic fuzzy set (IFS), interval valued intuitionistic fuzzy set (IVIFS), Pythagorean fuzzy set (PFS) etc. are employed in the existing literature. This paper utilizes an advanced extension of fuzzy sets, known as Interval-Valued Pythagorean Fuzzy Sets (IVPFS) in transportation models. IVPFS provides a more flexible framework by allowing the MD & NMD to be interval values to capture a wider range of uncertainty. This paper introduces a novel score function dealing with IVPFS to enhance the decision-making processes in uncertain environments. As compare to the other score function of IVPFS, the proposed score function provide us more optimal results. which is also helpful to evaluate more optimal cost of PFTP. Also, the proposed score function integrates these interval values to quantify and rank the alternatives more effectively.However, a notable trade-off is the increased computational complexity due to the use of interval values in the membership and non-membership functions, particularly in larger-scale transportation problems. Furthermore, the different models (Type-1, Type-2 and Type-3) show varied effectiveness in different scenarios: Type-1 performs best when cost uncertainty is primary, Type-2 is suitable when both supply and demand are uncertain and Type-3 addresses all three factors-supply, demand and cost-under uncertainty.Three types of interval valued Pythagorean fuzzy transportation problems (IVPFTP) are examined in this study: Type-1 considers cost in a Pythagorean fuzzy nature, Type-2 addresses both supply and demand in a Pythagorean fuzzy nature and Type-3 incorporates supply, demand and cost all are in a Pythagorean fuzzy nature. Through comprehensive numerical analysis, In Type-1 IVPFTP the cost dropped from 5.19 to 0.675, for Type-2 IVPFTP cost dropped from 0.2615 to 0.001869 and for Type-3 IVPFTP cost dropped from0.17435 to 0.0013879.Thereafter, it was observed that the proposed score function provides a more optimal transportation cost.Also, our findings demonstrate the significant cost reductions and improved decision-making capabilities across different types of IVPFTP models to highlight the efficiency of the proposed score function in handling uncertainty within the transportation problems.http://www.sciencedirect.com/science/article/pii/S2590123025001367Intuitionistic fuzzy setPythagorean fuzzy setinterval valued Pythagorean fuzzy setScore functionTransportation problem
spellingShingle Ritu
Tarun Kumar
Jahnvi
Kapil Kumar
Nitesh Dhiman
M.K. Sharma
Novel Pythagorean fuzzy score function to optimize fuzzy transportation models
Results in Engineering
Intuitionistic fuzzy set
Pythagorean fuzzy set
interval valued Pythagorean fuzzy set
Score function
Transportation problem
title Novel Pythagorean fuzzy score function to optimize fuzzy transportation models
title_full Novel Pythagorean fuzzy score function to optimize fuzzy transportation models
title_fullStr Novel Pythagorean fuzzy score function to optimize fuzzy transportation models
title_full_unstemmed Novel Pythagorean fuzzy score function to optimize fuzzy transportation models
title_short Novel Pythagorean fuzzy score function to optimize fuzzy transportation models
title_sort novel pythagorean fuzzy score function to optimize fuzzy transportation models
topic Intuitionistic fuzzy set
Pythagorean fuzzy set
interval valued Pythagorean fuzzy set
Score function
Transportation problem
url http://www.sciencedirect.com/science/article/pii/S2590123025001367
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AT jahnvi novelpythagoreanfuzzyscorefunctiontooptimizefuzzytransportationmodels
AT kapilkumar novelpythagoreanfuzzyscorefunctiontooptimizefuzzytransportationmodels
AT niteshdhiman novelpythagoreanfuzzyscorefunctiontooptimizefuzzytransportationmodels
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