Uncertainty quantification with risk measures in production planning

DOI10.1186/s13362-020-00074-4zbMath1472.90034arXiv1905.05014OpenAlexW3029602877MaRDI QIDQ1980955

Stephan Knapp, Simone Goettlich

Publication date: 9 September 2021

Published in: Journal of Mathematics in Industry (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1905.05014

zbMATH Keywords

uncertainty quantificationproduction networkscoupled PDE-ODE system

Mathematics Subject Classification ID

Applications of statistics in engineering and industry; control charts (62P30) Stochastic network models in operations research (90B15) Production models (90B30)

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Cites Work

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• Stochastic finance. An introduction in discrete time.
• Optimal production planning for assembly systems with uncertain capacities and random demand
• Time-continuous production networks with random breakdowns
• Semi-Markovian capacities in production network models
• Network models for supply chains
• A continuous buffer allocation model using stochastic processes
• Coherent Measures of Risk
• Bayesian Calibration of Computer Models
• Existence and Optimality Conditions for Risk-Averse PDE-Constrained Optimization
• Modeling, Simulation, and Optimization of Supply Chains
• Control of Continuum Models of Production Systems
• Load-Dependent Machine Failures in Production Network Models
• Data-Fitted Second-Order Macroscopic Production Models
• Risk-Averse PDE-Constrained Optimization Using the Conditional Value-At-Risk