Computational analysis of stochastic and robust optimization models for capacitated lot sizing under uncertain customer demand
Sprache des Vortragstitels:
Manufacturing and Service Operations Management Conference 2022
Sprache des Tagungstitel:
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.