48 citations · 94 across the 11 of their papers we have counts for
11 papers
Learning to Reformulate for Linear Programming
Xijun Li, Qingyu Qu, Fangzhou Zhu +4
It has been verified that the linear programming (LP) is able to formulate many real-life optimization problems, which can obtain the optimum by resorting to corresponding solvers…
Context-aware Telco Outdoor Localization
Yige Zhang, Weixiong Rao, Mingxuan Yuan +2
Recent years have witnessed the fast growth in telecommunication (Telco) techniques from 2G to upcoming 5G. Precise outdoor localization is important for Telco operators to manage,…
Grassland: A Rapid Algebraic Modeling System for Million-variable Optimization
Xihan Li, Xiongwei Han, Zhishuo Zhou +3
An algebraic modeling system (AMS) is a type of mathematical software for optimization problems, which allows users to define symbolic mathematical models in a specific language, i…
Learning-Aided Heuristics Design for Storage System
Yingtian Tang, Han Lu, Xijun Li +3
Computer systems such as storage systems normally require transparent white-box algorithms that are interpretable for human experts. In this work, we propose a learning-aided heuri…
Learning to Optimize Industry-Scale Dynamic Pickup and Delivery Problems
Xijun Li, Weilin Luo, Mingxuan Yuan +5
The Dynamic Pickup and Delivery Problem (DPDP) is aimed at dynamically scheduling vehicles among multiple sites in order to minimize the cost when delivery orders are not known a p…
Learning to Optimize DAG Scheduling in Heterogeneous Environment
Jinhong Luo, Yunfan Zhou, Xijun Li +3
Scheduling job flows efficiently and rapidly on distributed computing clusters is one of huge challenges for daily operation of data centers. In a practical scenario, a single job…
Bilevel Learning Model Towards Industrial Scheduling
Longkang Li, Hui-Ling Zhen, Mingxuan Yuan +5
Automatic industrial scheduling, aiming at optimizing the sequence of jobs over limited resources, is widely needed in manufacturing industries. However, existing scheduling system…
DFSeer: A Visual Analytics Approach to Facilitate Model Selection for Demand Forecasting
Dong Sun, Zezheng Feng, Yuanzhe Chen +5
Selecting an appropriate model to forecast product demand is critical to the manufacturing industry. However, due to the data complexity, market uncertainty and users' demanding re…
Block Hankel Tensor ARIMA for Multiple Short Time Series Forecasting
Qiquan Shi, Jiaming Yin, Jiajun Cai +5
This work proposes a novel approach for multiple time series forecasting. At first, multi-way delay embedding transform (MDT) is employed to represent time series as low-rank block…
Transfer Learning-Based Outdoor Position Recovery with Telco Data
Yige Zhang, Aaron Yi Ding, Jorg Ott +4
Telecommunication (Telco) outdoor position recovery aims to localize outdoor mobile devices by leveraging measurement report (MR) data. Unfortunately, Telco position recovery requi…
PlanningVis: A Visual Analytics Approach to Production Planning in Smart Factories
Dong Sun, Renfei Huang, Yuanzhe Chen +5
Production planning in the manufacturing industry is crucial for fully utilizing factory resources (e.g., machines, raw materials and workers) and reducing costs. With the advent o…