Neutrosophic Linear Programming (NLP) issues is presently extensive applications in science and engineering. The primary commitment right now to manage the NLP problem where the coefficients are neutrosophic triangular numbers with blended requirements.

Science is the basis for managing the affairs of life and human activities, and living without knowledge is a form of wandering and a kind of loss. Using scientific methods helps us understand the foundations of choice, decision-making, and adopting the right solutions when solutions abound and options are numerous. Operational research is considered the best that scientific development has provided because its methods depend on the application of scientific methods in solving complex issues and the optimal use of available resources in various fields, private and governmental work in peace and war, in politics and economics, in planning and implementation, and in various aspects of life. Its basic essence is to use the data provided for the issue under study to build a mathematical model that is the optimal solution. It is the basis on which decision makers rely in managing institutions and companies, and when operations research methods meet with the neutrosophic teacher, we get ideal solutions that take into account all the circumstances and fluctuations that may occur in the work environment over time. One of the most important operations research methods is the linear programming method. Which prompted us to reformulate the linear models, the graphical method, and the simplex method, which are used to obtain the optimal solution for linear models using the concepts of neutrosophic science. In this research, and as a continuation of what we presented previously, we will reformulate the modified simplex algorithm that was presented to address the difficulty that we were facing when applying the direct simplex algorithm. It is the large number of calculations required to be performed in each step of the solution, which requires a lot of time and effort.

The science of operations research is the applied aspect of mathematics and one of the most important modern sciences that is concerned with practical issues and meets the desire and request of decision makers to obtain ideal decisions through the methods it presents that are appropriate for all issues, such as linear programming, nonlinear programming, dynamic programming, integer programming, etc. The basic essence of this science is to build mathematical models consisting of an objective function and constraints. In these models, the objective function is a maximization function or a minimization function for a specific quantity. This quantity depends on a number of decision variables that may be independent of each other or related to each other. Through a set of constraints, we obtain values for these variables by solving the mathematical model that we obtain. Given the great importance of operations research methods, we have in previous research presented a neutrosophic vision for some of these methods, such as neutrosophic linear models, neutrosophic nonlinear models, dynamic programming, neutrosophic programming with binary integers, etc. In this research, we present a neutrosophical study of some of the procedures used to convert some zero-one neutrosophic nonlinear programming problems into zero-one neutrosophic linear programming problems.

This paper develops a general form of neutrosophic linear fractional programming (NLFP) problem and proposed a novel model to solve it. In this method the NLFP problem is decomposed into two neutrosophic linear programming (NLP) problem. Furthermore, the problem has been solved by combination of dual simplex method and a special ranking function. In addition, the model is compared with an existing method. An illustrative example is shown for better understanding of the proposed method. The results show that the method is computationally very simple and comprehensible.

Smarandache presented neutrosophic theory as a tool for handling undetermined information, and together with Wang et al. introduced single valued neutrosophic sets that is a special neutrosophic set and can be used expediently to deal with real-world problems, especially in decision support. In this paper, we propose linear programming problems based on neutrosophic environment. Neutrosophic sets characterized by three independent parameters, namely truth-membership degree (T), indeterminacy-membership degree (I) and falsity-membership degree (F), which is more capable to handle imprecise parameters. We also transform the neutrosophic linear programming problem into a crisp programming model by using neutrosophic set parameters. To measure the efficiency of our proposed model we solved several numerical examples.

“Neutrosophic Sets and Systems” has been created for publications on advanced studies in neutrosophy, neutrosophic set, neutrosophic logic, neutrosophic probability, neutrosophic statistics that started in 1995 and their applications in any field, such as the neutrosophic structures developed in algebra, geometry, topology, etc. In this issue: On Neutrosophic Crisp Sets and Neutrosophic Crisp Mathematical Morphology, New Results on Pythagorean Neutrosophic Open Sets in Pythagorean Neutrosophic Topological Spaces, Comparative Mathematical Model for Predicting of Financial Loans Default using Altman Z-Score and Neutrosophic AHP Methods.

Papers on neutrosophic programming, neutrosophic hypersoft set, neutrosophic topological spaces, NeutroAlgebra, NeutroGeometry, AntiGeometry, NeutroNearRings, neutrosophic differential equations, etc.