We consider a multi-player optimization where each player has her own optimization problem and the individual problems are connected by a cardinality constraint on their shared resources. We give distributed algorithms that allow each player to solve their own optimization problem and still achieve a global optimization solution for problems that possess a concavity property. For problems without the concavity property, we use concave approximating functions to bound the optimality error and provide empirical results on the deviations from optimality.

中文翻译：

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具有耦合基数约束的分布式整数规划问题的分散算法

我们考虑了一个多玩家优化，其中每个玩家都有自己的优化问题，并且各个问题都通过对其共享资源的基数约束而联系在一起。我们提供了分布式算法，可以使每个玩家解决自己的优化问题，并仍然针对具有凹性的问题实现全局优化解决方案。对于没有凹性的问题，我们使用凹面逼近函数来约束最优误差，并提供与最优偏差的经验结果。