Iterative Prediction-and-Optimization for E-Logistics Distribution Network Design

DOI10.1287/ijoc.2021.1107zbMath1492.90020OpenAlexW3166686099MaRDI QIDQ5085989

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Publication date: 30 June 2022

Published in: INFORMS Journal on Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1287/ijoc.2021.1107

zbMATH Keywords

heuristicartificial neural networkdemand predictionfacility location optimizatione-logistics

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Mixed integer programming (90C11) Linear programming (90C05) Transportation, logistics and supply chain management (90B06) Approximation methods and heuristics in mathematical programming (90C59) Dynamic programming (90C39) Discrete location and assignment (90B80)

Uses Software

• Genocop
• AdaBoost.RT
• TensorFlow

Cites Work

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• On the convergence properties of the EM algorithm
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• Trends in transportation and logistics
• Warehousing in the e-commerce era: a survey
• Multi-level facility location problems
• Product sales forecasting using macroeconomic indicators and online reviews: a method combining prospect theory and sentiment analysis
• Exact algorithms based on Benders decomposition for multicommodity uncapacitated fixed-charge network design
• A survey of randomized algorithms for training neural networks
• Benders Decomposition for Large-Scale Uncapacitated Hub Location

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