We apply the t-linearization technique to the maximum diversity problem (MDP) and compare its performance with other well-known linearizations. We lift the t-constraints based on the cardinality restriction, derive valid inequalities for MDP, and show their usefulness to solve the problem within the t-linearization framework. We propose and computationally evaluate a branch-and-bound algorithm on benchmark instances. The algorithm is compared with other exact approaches from the literature.

中文翻译：

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t-最大分集问题的线性化

我们将t线性化技术应用于最大分集问题（MDP），并将其性能与其他众所周知的线性化进行比较。我们基于基数限制解除t约束，导出MDP的有效不等式，并显示它们在t线性化框架内解决问题的有用性。我们提出并通过计算评估基准实例上的分支定界算法。将该算法与文献中的其他精确方法进行了比较。