A neural network to solve quadratic programming problems with fuzzy parameters

Amin Mansoori (), Sohrab Effati () and Mohammad Eshaghnezhad ()
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Amin Mansoori: Ferdowsi University of Mashhad
Sohrab Effati: Ferdowsi University of Mashhad
Mohammad Eshaghnezhad: Ferdowsi University of Mashhad

Fuzzy Optimization and Decision Making, 2018, vol. 17, issue 1, No 4, 75-101

Abstract: Abstract In this paper, a representation of a recurrent neural network to solve quadratic programming problems with fuzzy parameters (FQP) is given. The motivation of the paper is to design a new effective one-layer structure neural network model for solving the FQP. As far as we know, there is not a study for the neural network on the FQP. Here, we change the FQP to a bi-objective problem. Furthermore, the bi-objective problem is reduced to a weighting problem and then the Lagrangian dual is constructed. In addition, we consider a neural network model to solve the FQP. Finally, some illustrative examples are given to show the effectiveness of our proposed approach.

Keywords: Quadratic programming problem with fuzzy parameters; Neural network model; Fuzzy mapping; Bi-objective problem; Weighting problem (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10700-016-9261-9

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