A signomial programming-based approach for multi-echelon supply chain disruption risk assessment with robust dynamic Bayesian network

DOI10.1016/j.cor.2023.106422OpenAlexW4386630085MaRDI QIDQ6065614

Feng Chu, Chengbin Chu, Hao Tang, Feifeng Zheng, Ming Liu, Yueyu Ding

Publication date: 15 November 2023

Published in: Computers \& Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cor.2023.106422

zbMATH Keywords

Bayesian networksdisruption risksignomial programmingripple effectdata scarcity

Mathematics Subject Classification ID

Operations research and management science (90Bxx)

Cites Work

• Global optimization of signomial geometric programming problems
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• A tutorial on geometric programming
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• Steady-state optimization of biochemical systems through geometric programming
• Optimal control of unknown nonaffine nonlinear discrete-time systems based on adaptive dynamic programming
• MM algorithms for geometric and signomial programming
• Probability