Solving fully neutrosophic linear programming problem with application to stock portfolio selection

Autor:	Hamiden Abd El-Wahed Khalifa, Pavan Kumar
Jazyk:	angličtina
Rok vydání:	2020
Předmět:	linear programming neutrosophic programming single-valued trapezoidal neutrosophic numbers score function stock profit Applied mathematics. Quantitative methods T57-57.97
Zdroj:	Croatian Operational Research Review, Vol 11, Iss 2, Pp 165-176 (2020)
Druh dokumentu:	article
ISSN:	1848-0225 1848-9931
DOI:	10.17535/crorr.2020.0014
Popis:	Neutrosophic set is considered as a generalized of crisp set, fuzzy set, and intuitionistic fuzzy set for representing the uncertainty, inconsistency, and incomplete knowledge about the real world problems. In this paper, a neutrosophic linear programming (NLP) problem with single-valued trapezoidal neutrosophic numbers is formulated and solved. A new method based on the so-called score function to find the neutrosophic optimal solution of fully neutrosophic linear programming (FNLP) problem is proposed. This method is more flexible than the linear programming (LP) problem, where it allows the decision maker to choose the preference he is willing to take. A stock portfolio problem is introduced as an application. Also, a numerical example is given to illustrate the utility and practically of the method.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/0f4c46b5f6ef48e7b1b97e7a03ffa2c9 Zobrazit plný text záznamu View record in DOAJ