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Dergiler / Middle East Journal of Science / 2023 / Volume: 9 Issue: 2

A LAGRANGE NEURAL NETWORK FOR NETWORK TRAFFIC ASSIGNMENT OPTIMIZATION

Hasan Dalman(BATMAN ÜNİVERSİTESİ)0009-0008-6574-3215
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Yayın Tarihi
2023-12-29
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⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

Finally, a numerical method are used to demonstrate that the results obtained from this neural network are a solution to the optimization problem and converge to user equilibrium.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:This study considers a nonlinear optimization problem used to achieve user equilibrium in the network traffic assignment problem.
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Temel Bulgular & Veri:By providing the Karush Kuhn Tucker conditions of this optimization problem, it is converted into a system of differential equations using the Lagrange function.
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Sonuç & Katkı:Finally, a numerical method are used to demonstrate that the results obtained from this neural network are a solution to the optimization problem and converge to user equilibrium.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Network traffic assignment · graph theory · dynamical systems

Abstract

This study considers a nonlinear optimization problem used to achieve user equilibrium in the network traffic assignment problem. By providing the Karush Kuhn Tucker conditions of this optimization problem, it is converted into a system of differential equations using the Lagrange function. This system is then redefined as a Lagrange neural network, which is proven to be asymptotically and lyapunov stable. Finally, a numerical method are used to demonstrate that the results obtained from this neural network are a solution to the optimization problem and converge to user equilibrium.

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Bu Makaleye Atıf Yap

Dalman, H. (2023). A LAGRANGE NEURAL NETWORK FOR NETWORK TRAFFIC ASSIGNMENT OPTIMIZATION. Middle East Journal of Science, Volume: 9 Issue: 2. https://doi.org/10.51477/mejs.1272077

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