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·
Y. Zhang
,
Min Huang
,
Z. Gao
Songchen Jiang
Songchen Jiang
,
S.C. Fang
,
X. Wang
· 1 分钟阅读时长
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
publications

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Songchen Jiang
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.