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Neutrosophic Number Optimization Models and Their Application in the Practical Production Process
Author(s) -
Angyan Tu,
Jun Ye,
Bing Wang
Publication year - 2021
Publication title -
journal of mathematics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.252
H-Index - 13
eISSN - 2314-4785
pISSN - 2314-4629
DOI - 10.1155/2021/6668711
Subject(s) - indeterminate , mathematical optimization , nonlinear programming , matlab , mathematics , simple (philosophy) , process (computing) , production (economics) , function (biology) , nonlinear system , computer science , epistemology , quantum mechanics , evolutionary biology , biology , pure mathematics , economics , macroeconomics , operating system , philosophy , physics
In order to simplify the complex calculation and solve the difficult solution problems of neutrosophic number optimization models (NNOMs) in the practical production process, this paper presents two methods to solve NNOMs, where Matlab built-in function “fmincon()” and neutrosophic number operations (NNOs) are used in indeterminate environments. Next, the two methods are applied to linear and nonlinear programming problems with neutrosophic number information to obtain the optimal solution of the maximum/minimum objective function under the constrained conditions of practical productions by neutrosophic number optimization programming (NNOP) examples. Finally, under indeterminate environments, the fit optimal solutions of the examples can also be achieved by using some specified indeterminate scales to fulfill some specified actual requirements. The NNOP methods can obtain the feasible and flexible optimal solutions and indicate the advantage of simple calculations in practical applications.

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