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Published in: Neural Computing and Applications 5/2019

06-03-2018 | S.I. : Emerging Intelligent Algorithms for Edge-of-Things Computing

A novel method for solving the fully neutrosophic linear programming problems

Authors: Mohamed Abdel-Basset, M. Gunasekaran, Mai Mohamed, Florentin Smarandache

Published in: Neural Computing and Applications | Issue 5/2019

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Abstract

The most widely used technique for solving and optimizing a real-life problem is linear programming (LP), due to its simplicity and efficiency. However, in order to handle the impreciseness in the data, the neutrosophic set theory plays a vital role which makes a simulation of the decision-making process of humans by considering all aspects of decision (i.e., agree, not sure and disagree). By keeping the advantages of it, in the present work, we have introduced the neutrosophic LP models where their parameters are represented with a trapezoidal neutrosophic numbers and presented a technique for solving them. The presented approach has been illustrated with some numerical examples and shows their superiority with the state of the art by comparison. Finally, we conclude that proposed approach is simpler, efficient and capable of solving the LP models as compared to other methods.

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Metadata
Title
A novel method for solving the fully neutrosophic linear programming problems
Authors
Mohamed Abdel-Basset
M. Gunasekaran
Mai Mohamed
Florentin Smarandache
Publication date
06-03-2018
Publisher
Springer London
Published in
Neural Computing and Applications / Issue 5/2019
Print ISSN: 0941-0643
Electronic ISSN: 1433-3058
DOI
https://doi.org/10.1007/s00521-018-3404-6

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