High-resolution Fuzzy Component Scheme for Second-order Differential Equation Appearing in Single Commodity Stochastic Production Planning
Navnit Jha, Irina Perfilieva, Kritika
Department of Mathematics, South Asian University, Chanakyapuri, New Delhi, India - 110021, Email: navnitjha@sau.ac.in, Institute for Research and Applications of Fuzzy Modeling, University of Ostrava, Ostrava, Czech Republic, Email: Irina.Perfilieva@osu.cz, Department of Mathematics, South Asian University, Chanakyapuri, New Delhi, India - 110021, Email: kritikagpt95@gmail.com
Received in final form on June 22, 2021
Abstract
The article deals with the second-order nonlinear differential equation that models stochastic production planning. We describe a fuzzy
transform technique for obtaining the approximate analytic solution to a single commodity stochastic production-inventory model. In general, the
classical solution is not known; thus, numerical treatment helps to analyze optimal inventory levels. The present description implements a fuzzy
transform that approximates solutions at the interior of the domain with high-order accuracy. The approximate fuzzy components implementing a
sinusoidal basic function are arranged with a three-point solution value. A non-singular matrix system relates the solution values and approximate fuzzy components, thus optimizing accuracy to fuzzy components affects the solution exactness. If the exact solution is known, the estimates of error are monitored by integrated absolute error for approximate analytical solutions. If the exact analytic solution is unknown, the approximate analytic closed-form solution by using spline interpolation is an additional reward to the scheme.
Keywords
Stochastic optimal control, production-inventory model, fuzzy transform, compact scheme, consistency, convergence rate.
Cite This Article
Navnit Jha, Irina Perfilieva, Kritika, High-resolution Fuzzy Component Scheme for
Second-order Differential Equation Appearing in Single Commodity Stochastic Production
Planning, J.Innovation Sciences and Sustainable Technologies, 1(3)(2021), 205 - 220. https://doie.org/10.0608/JISST.2022448367
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