International Journal of Neutrosophic Science
  IJNS
  2690-6805
  2692-6148
  
   10.54216/IJNS
   https://www.americaspg.com/journals/show/3980
  
 
 
  
   2020
  
  
   2020
  
 
 
  
   Improvement to the Gradient Projection Method Used to Find the Optimal Solution for Neutrosophic Nonlinear Models Constrained by Equality Constraints
  
  
   Faculty of Science, Damascus University, Damascus, Syria; Department of Requirements, International University for Science and Technology, Ghabageb, Syrian Arab Republic
   
    Maissam
    Maissam
   
   University of New MexicoŘ Mathematics, Physics and Natural Sciences Division 705 Gurley Ave., Gallup, NM 87301, USA
   
    Florentin
    Smarandache
   
  
  
   A mathematical model consists of decision variables, a goal function, and constraints. The region of possible solutions for a nonlinear mathematical model is the set of vectors whose components satisfy all constraints. The optimal solution is the vector whose components satisfy all constraints, and at which the function reaches an optimal value (maximum or minimum). Nonlinear programming constitutes an important and fundamental part of operations research and is more comprehensive than linear programming. Its applications have spread across all branches of science, including engineering, physics, chemistry, management, economics, and military fields, among others. Nonlinear programming can also be used in forecasting, estimation, applied statistics, and determining the costs resulting from the production, purchase, and storage of goods. Given this importance, and in order to obtain a more accurate solution that takes into account all the changes that the system under study may be exposed to, we have previously presented a neutrosophic study of nonlinear models and some of the methods used to find the optimal solution. In addition to what we have previously done, in a research we present an improvement to the gradient projection method used to find the optimal solution for nonlinear models constrained by equal constraints, enabling us to obtain the optimal solution in fewer steps. We will then apply it to find the solution. Optimization of nonlinear neutrosophic models.
  
  
   2026
  
  
   2026
  
  
   159
   175
  
  
   10.54216/IJNS.270116
   https://www.americaspg.com/articleinfo/21/show/3980