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arXiv · 2202.02725

Efficient primal heuristics for mixed-integer linear programs

Akang Wang·Linxin Yang·Sha Lai·Xiaodong Luo·Xiang Zhou·Haohan Huang·Shengcheng Shao·Yuanming Zhu·Dong Zhang·Tao Quan
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Abstract

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 efficiently identify high-quality feasible solutions. The computational studies demonstrate the superiority of our proposed approaches over the competitors'.

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Akang Wang, Linxin Yang, Sha Lai, Xiaodong Luo, Xiang Zhou, Haohan Huang, Shengcheng Shao, Yuanming Zhu, Dong Zhang, Tao Quan. 2022-02-06. Efficient primal heuristics for mixed-integer linear programs. https://arxiv.org/abs/2202.02725

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