%0 Journal Article %T Finding Optimal Solutions to a Class of Parametric Optimization Problems in Terms of Parameter Values by using Multilayer Neural Networks %J Journal of Advanced Mathematical Modeling %I Shahid Chamran University of Ahvaz %Z 2251-8088 %A Mohammadsalahi, Kobra %A Modarres Khyiabani, Farzin %A Azarmir, Nima %D 2021 %\ 12/22/2021 %V 11 %N 4 %P 611-625 %! Finding Optimal Solutions to a Class of Parametric Optimization Problems in Terms of Parameter Values by using Multilayer Neural Networks %K Parametric Optimization&lrm %K Multilayer Neural Networks&lrm %K Recurrent Neural Networks&lrm %K &lrm %K Free Derivative Optimizatiuon %R 10.22055/jamm.2021.37931.1944 %X ‎‎In this paper, parametric optimization problems are investigated. ‎In a‎ ‎parametric ‎optimization ‎problem ‎we ‎assume ‎‏‎$‎‎‎‎‎‏‎‎lambda‎in‎mathbb{R}^n‎$‎‎ ‎is ‎the ‎vector ‎of ‎the ‎parameters ‎and ‎‎$‎‎x^*$ ‎is ‎the ‎optimal ‎answer ‎corresponding ‎to ‎it. ‎The ‎purpose ‎of ‎this ‎paper ‎is ‎to ‎determine a‎ ‎function ‎such ‎as ‎‎$‎‎psi$ ‎so ‎that ‎we ‎have ‎‎$‎‎psi(‎lambda‎)=x^*$.‎ To do this, first for each ‎$‎‎‎lambda‎$‎, the corresponding optimal answer is calculated. In this way, a set of data bases consisting of parameters and the corresponding optimal values are obtained. A multilayer network of data base is trained to obtain the function ‎$‎‎psi$‎ in a domain. In fact, the function ‎$‎‎psi$‎ for each value of the parameter specifies the corresponding answer by the trained multilayer network.‎‎ Finally, we conduct several numerical examples to test our method. %U https://jamm.scu.ac.ir/article_17114_756662f0f15bee04704baacda011cb7f.pdf