Zobrazeno 1 - 10
of 34
pro vyhledávání: '"Wang, Akang"'
Solving constrained nonlinear programs (NLPs) is of great importance in various domains such as power systems, robotics, and wireless communication networks. One widely used approach for addressing NLPs is the interior point method (IPM). The most co
Externí odkaz:
http://arxiv.org/abs/2410.15731
Autor:
Chen, Qian, Zhang, Tianjian, Yang, Linxin, Han, Qingyu, Wang, Akang, Sun, Ruoyu, Luo, Xiaodong, Chang, Tsung-Hui
Integer linear programs (ILPs) are commonly employed to model diverse practical problems such as scheduling and planning. Recently, machine learning techniques have been utilized to solve ILPs. A straightforward idea is to train a model via supervise
Externí odkaz:
http://arxiv.org/abs/2409.19678
Autor:
Li, Bingheng, Yang, Linxin, Chen, Yupeng, Wang, Senmiao, Chen, Qian, Mao, Haitao, Ma, Yao, Wang, Akang, Ding, Tian, Tang, Jiliang, Sun, Ruoyu
Solving large-scale linear programming (LP) problems is an important task in various areas such as communication networks, power systems, finance and logistics. Recently, two distinct approaches have emerged to expedite LP solving: (i) First-order me
Externí odkaz:
http://arxiv.org/abs/2406.01908
Inventory management, vehicle routing, and delivery scheduling decisions are simultaneously considered in the context of the inventory routing problem. This paper focuses on the continuous-time version of this problem where, unlike its more tradition
Externí odkaz:
http://arxiv.org/abs/2310.11240
Autor:
Han, Qingyu, Yang, Linxin, Chen, Qian, Zhou, Xiang, Zhang, Dong, Wang, Akang, Sun, Ruoyu, Luo, Xiaodong
Mixed-integer linear programming (MILP) is widely employed for modeling combinatorial optimization problems. In practice, similar MILP instances with only coefficient variations are routinely solved, and machine learning (ML) algorithms are capable o
Externí odkaz:
http://arxiv.org/abs/2302.05636
Autor:
Gasse, Maxime, Cappart, Quentin, Charfreitag, Jonas, Charlin, Laurent, Chételat, Didier, Chmiela, Antonia, Dumouchelle, Justin, Gleixner, Ambros, Kazachkov, Aleksandr M., Khalil, Elias, Lichocki, Pawel, Lodi, Andrea, Lubin, Miles, Maddison, Chris J., Morris, Christopher, Papageorgiou, Dimitri J., Parjadis, Augustin, Pokutta, Sebastian, Prouvost, Antoine, Scavuzzo, Lara, Zarpellon, Giulia, Yang, Linxin, Lai, Sha, Wang, Akang, Luo, Xiaodong, Zhou, Xiang, Huang, Haohan, Shao, Shengcheng, Zhu, Yuanming, Zhang, Dong, Quan, Tao, Cao, Zixuan, Xu, Yang, Huang, Zhewei, Zhou, Shuchang, Binbin, Chen, Minggui, He, Hao, Hao, Zhiyu, Zhang, Zhiwu, An, Kun, Mao
Combinatorial optimization is a well-established area in operations research and computer science. Until recently, its methods have focused on solving problem instances in isolation, ignoring that they often stem from related data distributions in pr
Externí odkaz:
http://arxiv.org/abs/2203.02433
Autor:
Wang, Akang, Yang, Linxin, Lai, Sha, Luo, Xiaodong, Zhou, Xiang, Huang, Haohan, Shao, Shengcheng, Zhu, Yuanming, Zhang, Dong, Quan, Tao
This paper is a short report about our work for the primal task in the Machine Learning for Combinatorial Optimization NeurIPS 2021 Competition. For each dataset of our interest in the competition, we propose customized primal heuristic methods to ef
Externí odkaz:
http://arxiv.org/abs/2202.02725
Autor:
Silva, Victor A., Wang, Akang, Filho, Virgílio José Martins Ferreira, Gounaris, Chrysanthos E.
Publikováno v:
In Computers and Operations Research April 2024 164
Publikováno v:
Transportation Research Part B: Methodological, 117:296-317, 2018
We study the strategic decision-making problem of assigning time windows to customers in the context of vehicle routing applications that are affected by operational uncertainty. This problem, known as the Time Window Assignment Vehicle Routing Probl
Externí odkaz:
http://arxiv.org/abs/1806.03220
Publikováno v:
In European Journal of Operational Research 16 February 2021 289(1):93-106