Converting Some Zero One Neutrosophic Nonlinear Programming Problems Into Zero One Neutrosophic Linear Programming Problems
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Converting Some Zero-One Neutrosophic Nonlinear Programming Problems into Zero-One Neutrosophic Linear Programming Problems
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.
Neutrosophic Sets and Systems, vol. 66/2024
Author: Florentin Smarandache
language: en
Publisher: Infinite Study
Release Date: 2024-04-15
“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. Neutrosophic Set and Neutrosophic Logic are generalizations of the fuzzy set and respectively fuzzy logic (especially of intuitionistic fuzzy set and respectively intuitionistic fuzzy logic). In neutrosophic logic a proposition has a degree of truth (T), a degree of indeterminacy (I), and a degree of falsity (F), where T, I, F are standard or non-standard subsets of ]-0, 1+[.
Generating Neutrosophic Random Variables Based Gamma Distribution
In practical life, we encounter many systems that cannot be studied directly, either due to their high cost or because some of these systems cannot be studied directly. Therefore, we resort to the simulation method, which depends on applying the study to systems similar to real ones and then projecting these results if they are suitable for the real system. The simulation process requires a good understanding of probability distributions and the methods used to transform random numbers that follow a regular distribution in the field [0,1] into random variables that follow them, so that we can achieve the greatest possible benefit from the simulation process and obtain more accurate and appropriate results for all conditions that arise. In previous research, we presented a neutrosophical vision of the process of generating random numbers that follow a regular distribution in the field [0, 1] and some techniques used to generate random variables, such as the inverse transformation technique that was used to generate random variables that follow a uniform distribution in the domain [a, b] and the exponential distribution, the rejection and acceptance technique, which was used to generate random variables that follow the beta distribution, and the mixed technique, which was used to generate random variables that follow the Poisson distribution. In this research, we present a neutrosophic study to generate neutrosophic random variables that follow the gamma distribution, a distribution that is frequently used in engineering applications.