Multi-Period Fourth-Party Logistics Network Design from the Viability Perspective: A Double-Layer Q-Learning based Collaborative Hyper-Heuristic Algorithm
1月 1, 2024·,,
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1 分钟阅读时长
Y. Zhang
Min Huang
Z. Gao
Songchen Jiang
S.C. Fang
X. Wang
摘要
A viability-oriented multi-period fourth-party logistics network design model and learning-based hyper-heuristic algorithm.
类型
出版物
International Journal of Production Research
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Authors
Ph.D. Student in Operations Research
I am a joint Ph.D. student in the College of Information Science and Engineering at Northeastern University, China, supervised by Prof. Min Huang, and the Institute of Operations Research and Analytics at the National University of Singapore, supervised by Prof. Chung-Piaw Teo. My research lies at the intersection of data-driven optimization, distributionally robust optimization, stochastic modeling, and supply chain analytics. I am particularly interested in developing tractable optimization models and algorithms for decision-making under uncertainty, with applications in inventory systems, supply chain network design, logistics planning, and operations management.