Stochastic production planning: optimal control and analytical insights

This study investigates a stochastic production planning problem with a running cost composed of quadratic production costs and inventory-dependent costs. The objective is to minimize the expected cost until production stops when inventory reaches a specified level, subject to a boundary condition. Using probability space and Brownian motion, the Hamilton-Jacobi-Bellman (HJB) equation is derived, and optimal feedback control is obtained. The solution demonstrates desirable monotonicity and convexity properties under specific assumptions. An illustrative example further confirms these results with explicit function properties and a practical application.

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Publication Details

Journal
Journal of Management Analytics
Published
2026-06-29
DOI
https://doi.org/10.1080/23270012.2026.2669043
Primary Topic
Risk and Portfolio Optimization
Type
article
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article

Stochastic production planning: optimal control and analytical insights

Dragoş-Pǎtru Covei
Journal of Management Analytics
Risk and Portfolio Optimization
article

Stochastic production planning: optimal control and analytical insights

Dragoş-Pǎtru Covei
article en

Abstract

This study investigates a stochastic production planning problem with a running cost composed of quadratic production costs and inventory-dependent costs. The objective is to minimize the expected cost until production stops when inventory reaches a specified level, subject to a boundary condition. Using probability space and Brownian motion, the Hamilton-Jacobi-Bellman (HJB) equation is derived, and optimal feedback control is obtained. The solution demonstrates desirable monotonicity and convexity properties under specific assumptions. An illustrative example further confirms these results with explicit function properties and a practical application.

Journal of Management Analytics
Bucharest University of Economic Studies (RO)
Openalex Percentile: Top 99%
Risk and Portfolio Optimization
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