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A class of algorithms for mixed-integer bilevel min-max optimization

机译:一类用于混合整数双级最小-最大优化的算法

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In this paper, we introduce a new class of algorithms for solving the mixed-integer bilevel min-max optimization problem. This problem involves two players, a leader and a follower, who play a Stackelberg game. In particular, the leader seeks to minimize over a set of discrete variables the maximum objective that the follower can achieve. The complicating features of our problem are that a subset of the follower's decisions are restricted to be integer-valued, and that the follower's decisions are constrained by the leader's decisions. We first describe several bilevel min-max programs that can be used to obtain lower and upper bounds on the optimal objective value of the problem. We then present algorithms for this problem that finitely terminate with an optimal solution when the leader variables are restricted to take binary values. Finally, we report the results of a computational study aimed at evaluating the quality of our algorithms on two families of randomly generated problems.
机译:在本文中,我们介绍了一种新的算法来解决混合整数双级最小-最大优化问题。这个问题涉及到两个玩家,一个领导者和一个跟随者,他们玩Stackelberg游戏。尤其是,领导者试图在一组离散变量上最小化追随者可以实现的最大目标。我们问题的复杂特征是,追随者的决定的一个子集被限制为整数值,并且追随者的决定受到领导者的决定的约束。我们首先描述几个可用于获得问题的最佳目标值的上下限的双层最小-最大程序。然后,我们提出了针对该问题的算法,当前导变量被限制为采用二进制值时,该算法将以最优解有限终止。最后,我们报告了一项计算研究的结果,该研究旨在评估两个随机产生的问题系列的算法质量。

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