Computational analysis of stochastic and robust optimization models for capacitated lot sizing under uncertain customer demand

Description

This work presents a computational study of two-stage stochastic programming and budget-uncertainty robust optimization for capacitated lot-sizing under uncertain demand. To solve the stochastic models, a Benders decomposition approach is tailored to the problem. The tradeoff between computational time and performance on out-of-sample scenarios is investigated. Managerial insights are provided by analyzing the structure of the obtained production plans and the impact of flexibility in planning.

Period	27 Jun 2022
Event title	Manufacturing and Service Operations Management Conference 2022
Event type	Conference
Location	GermanyShow on map