Neutrosophic multi-objective green four-dimensional fixed-charge transportation problem

The main inquisition of this paper is to introduce two methods for solving a multi-objective green 4-dimensional fixed-charge transportation problem (MG4FTP) under neutrosophic environment. The increasing use of transportation vehicles, the condition of roads, vehicle type in daily life to meet our...

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Published in:International journal of machine learning and cybernetics Vol. 13; no. 10; pp. 3089 - 3112
Main Authors: Giri, Binoy Krishna, Roy, Sankar Kumar
Format: Journal Article
Language:English
Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2022
Springer Nature B.V
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ISSN:1868-8071, 1868-808X
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Abstract The main inquisition of this paper is to introduce two methods for solving a multi-objective green 4-dimensional fixed-charge transportation problem (MG4FTP) under neutrosophic environment. The increasing use of transportation vehicles, the condition of roads, vehicle type in daily life to meet our needs that create a lot of problems such as global warming, greenhouse gas (GHG) emissions in the nature. In this paper, we minimize transportation cost, carbon emission and transportation time. In real-life situation, all parameters of transportation problem are not tackled by crisp value, fuzzy numbers and intuitionistic fuzzy numbers, then to accommodate the fact we choice here single valued trapezoidal neutrosophic number (SVTNN) for designing such type of transportation problem. Thereafter we use α , β , γ -cut of SVTNN to convert the parameters in interval form of the proposed model. Two new approaches based on neutrosophic programming (NP) and Pythagorean hesitant fuzzy programming (PHFP) are used to extract a better compromise solution of the proposed problem. A comparison is drawn among the compromise solutions that are derived from the programming, by using the score function of SVTNN. Two numerical examples are included to illustrate the applicability and validity of the proposed problem.
AbstractList The main inquisition of this paper is to introduce two methods for solving a multi-objective green 4-dimensional fixed-charge transportation problem (MG4FTP) under neutrosophic environment. The increasing use of transportation vehicles, the condition of roads, vehicle type in daily life to meet our needs that create a lot of problems such as global warming, greenhouse gas (GHG) emissions in the nature. In this paper, we minimize transportation cost, carbon emission and transportation time. In real-life situation, all parameters of transportation problem are not tackled by crisp value, fuzzy numbers and intuitionistic fuzzy numbers, then to accommodate the fact we choice here single valued trapezoidal neutrosophic number (SVTNN) for designing such type of transportation problem. Thereafter we use α , β , γ -cut of SVTNN to convert the parameters in interval form of the proposed model. Two new approaches based on neutrosophic programming (NP) and Pythagorean hesitant fuzzy programming (PHFP) are used to extract a better compromise solution of the proposed problem. A comparison is drawn among the compromise solutions that are derived from the programming, by using the score function of SVTNN. Two numerical examples are included to illustrate the applicability and validity of the proposed problem.
The main inquisition of this paper is to introduce two methods for solving a multi-objective green 4-dimensional fixed-charge transportation problem (MG4FTP) under neutrosophic environment. The increasing use of transportation vehicles, the condition of roads, vehicle type in daily life to meet our needs that create a lot of problems such as global warming, greenhouse gas (GHG) emissions in the nature. In this paper, we minimize transportation cost, carbon emission and transportation time. In real-life situation, all parameters of transportation problem are not tackled by crisp value, fuzzy numbers and intuitionistic fuzzy numbers, then to accommodate the fact we choice here single valued trapezoidal neutrosophic number (SVTNN) for designing such type of transportation problem. Thereafter we use α,β,γ-cut of SVTNN to convert the parameters in interval form of the proposed model. Two new approaches based on neutrosophic programming (NP) and Pythagorean hesitant fuzzy programming (PHFP) are used to extract a better compromise solution of the proposed problem. A comparison is drawn among the compromise solutions that are derived from the programming, by using the score function of SVTNN. Two numerical examples are included to illustrate the applicability and validity of the proposed problem.
Author Roy, Sankar Kumar
Giri, Binoy Krishna
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  givenname: Sankar Kumar
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  surname: Roy
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Issue 10
Keywords 4-Dimensional fixed-charge transportation problem
Carbon emission
Single valued trapezoidal neutrosophic number
Multi-objective decision making
Neutrosophic programming and Pythagorean hesitant fuzzy programming
Score function
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SubjectTerms Artificial Intelligence
Carbon
Charge transport
Climate change
Complex Systems
Computational Intelligence
Control
Decision making
Electric vehicles
Emissions
Engineering
Fuzzy sets
Greenhouse effect
Greenhouse gases
Linear programming
Mechatronics
Natural gas vehicles
Original Article
Outdoor air quality
Parameters
Pattern Recognition
Programming
Robotics
Set theory
Systems Biology
Transportation problem
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Title Neutrosophic multi-objective green four-dimensional fixed-charge transportation problem
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