论文标题
使用双线性术语上限收紧基于离散化的MILP模型，用于合并问题
Tightening Discretization-based MILP Models for the Pooling Problem using Upper Bounds on Bilinear Terms
论文作者
论文摘要
已经提出了基于离散化的方法来解决双线性术语（例如汇总问题）的非凸优化问题。这些方法将原始的非凸优化问题转换为混合企业线性程序（MILP）。在本文中，我们研究了这些MILP模型的收紧方法，以解决合并问题，并使用双线性术语上的上限来得出有效的约束。计算结果证明了我们方法在减少解决方案时间方面的有效性。
Discretization-based methods have been proposed for solving nonconvex optimization problems with bilinear terms such as the pooling problem. These methods convert the original nonconvex optimization problems into mixed-integer linear programs (MILPs). In this paper we study tightening methods for these MILP models for the pooling problem, and derive valid constraints using upper bounds on bilinear terms. Computational results demonstrate the effectiveness of our methods in terms of reducing solution time.
