Yingdong Lu
IBM
84 Papers
599 Citations
Yingdong Lu is an academic researcher from IBM. The author has contributed to research in topics: Time horizon & Optimal control. The author has an hindex of 18, co-authored 84 publications.
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Papers
Order-Based Cost Optimization in Assemble-to-Order Systems
Yingdong Lu,Jing-Sheng Song +1 more
TL;DR: A cost-minimization model with order-based backorder costs is formulated and it is shown that the solution can be bounded by that of the latter with appropriately imputed parameters, and the optimal base-stock levels can be obtained in a greedy fashion.
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Asymptotic Optimality of Constant-Order Policies for Lost Sales Inventory Models with Large Lead Times
TL;DR: This paper shows that when lead times are large, a very simple constant-order policy, first studied by Reiman, performs nearly optimally and combines a novel coupling for suprema of random walks with arguments from queueing theory.
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No-Holdback Allocation Rules for Continuous-Time Assemble-to-Order Systems
TL;DR: This paper analyzes a class of common-component allocation rules, termed no-holdback (NHB) rules, in continuous-review assemble-to-order (ATO) systems with positive lead times, and identifies metrics as well as cost and product structures under which NHB rules outperform all other component allocation rules.
Patent
Method and structure for end-to-end workforce management
Heng Cao,John Matthew Collins,Daniel Patrick Connors,Donna L. Gresh,Meng-Chen Hsieh,Jianying Hu,Mark A. Eaton,Ta-Hsin Li,Yingdong Lu,Aleksandra Majsilovic,Ana Radovanovic,Bonnie K. Ray,Mark S. Squillante +12 more
- 10 Jan 2007
TL;DR: A workforce management tool includes an input section that receives data from one or more data sources that together reflect data of substantially an entirety of a workforce of an organization as discussed by the authors, and a plurality of service modules receive and process the data in accordance with requirements of different segments of the organization.
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Patent
Method and structure for bid winning probability estimation and pricing model
Heng Cao,Roger R. Gung,Yunhee Jang,Richard D. Lawrence,Grace Lin,Yingdong Lu +5 more
- 12 Apr 2002
TL;DR: In this paper, a method for developing a distribution function for the probability of winning a bid by a seller for a product or service, using the seller's own historical data for winning bids and lost bids, is presented.
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