Mathematical optimization of inventory control systems with random demand and dynamic constraints
Author(s): Vittal Gondkar and Harsh Vardhan
Abstract: This paper introduces a comprehensive mathematical approach to inventory control systems with a focus on handling random demand patterns and dynamic constraints. Using a combination of stochastic processes, differential equations, and optimization theory, we develop new models for inventory replenishment, pricing, and demand forecasting. This study applies tools from Markov decision processes (MDP), queueing theory, and convex optimization to derive solutions that minimize costs while ensuring service-level efficiency. We validate the models through computational simulations, demonstrating their applicability to industries with unpredictable demand and high variability.
Vittal Gondkar, Harsh Vardhan. Mathematical optimization of inventory control systems with random demand and dynamic constraints. Int J Stat Appl Math 2025;10(6):154-156. DOI: 10.22271/maths.2025.v10.i6b.2069
