A novel method for solving the fully neutrosophic linear programming problems

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

Research output: Contribution to journalArticlepeer-review

108 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)1595-1605
Number of pages11
JournalNeural Computing and Applications
Volume31
Issue number5
DOIs
Publication statusPublished - 3 May 2019
Externally publishedYes

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