# Uncertainty quantification with risk measures in production planning

## TL;DR

This paper develops a simulation-based optimization framework for production planning under uncertainty, using risk measures inspired by finance to evaluate system performance amid random capacity fluctuations and workforce availability.

## Contribution

It introduces a novel application of finance-inspired risk measures to stochastic production and workforce planning problems, integrating them into a simulation-based optimization approach.

## Key findings

- Effective risk measures for production capacity variability
- Insights into workforce availability impacts
- Framework adaptable to various uncertain environments

## Abstract

This paper is concerned with a simulation study for a stochastic production network model, where the capacities of machines may change randomly. We introduce performance measures motivated by risk measures from finance leading to a simulation based optimization framework for the production planning. The same measures are used to investigate the scenario when capacities are related to workers that are randomly not available. This corresponds to the study of a workforce planning problem in an uncertain environment.