An Optimization-Based Framework for Process Planning under Uncertainty with Risk Management

In the current challenging and volatile political and economic environment, the process industry is exposed to a high degree of uncertainty that renders the production planning task to be a risky and complex optimization problem requiring high computational expense. This work proposes a computationally-tractable optimization-based framework for risk management in midterm process planning under uncertainty. We employ stochastic programming to …