An efficient algorithm for stochastic optimal control problems by means of a least-squares Monte-Carlo method

DOI10.1080/02331934.2021.2009824zbMath1505.93280OpenAlexW4200152604MaRDI QIDQ5044095

Fikriye Yılmaz, Hacer Öz Bakan, Gerhard-Wilhelm Weber

Publication date: 24 October 2022

Published in: Optimization (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331934.2021.2009824

zbMATH Keywords

optimizationstochastic optimal controlRunge-Kutta methoddiscrete optimality conditionsleast-squares Monte Carlo method

Mathematics Subject Classification ID

Least squares and related methods for stochastic control systems (93E24) Optimal stochastic control (93E20)

Cites Work

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• Conjugate convex functions in optimal stochastic control
• Minimal truncation error constants for Runge-Kutta method for stochastic optimal control problems
• On the grey obligation rules
• Euler-Maruyama scheme for Caputo stochastic fractional differential equations
• Strong-order conditions of Runge-Kutta method for stochastic optimal control problems
• A multi-objective invasive weed optimization algorithm for robust aggregate production planning under uncertain seasonal demand
• Optimal control without solving the Bellman equation
• Discrete-time approximation and Monte-Carlo simulation of backward stochastic differential equations
• Controlled Markov processes and viscosity solutions
• Stability of Regression-Based Monte Carlo Methods for Solving Nonlinear PDEs
• A General Stochastic Maximum Principle for Optimal Control Problems
• An Introductory Approach to Duality in Optimal Stochastic Control

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