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Parametric global optimisation for bilevel programming

机译:用于双层编程的参数全局优化

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We propose a global optimisation approach for the solution of various classes of bilevel programming problems (BLPP) based on recently developed parametric programming algorithms. We first describe how we can recast and solve the inner (follower's) problem of the bilevel formulation as a multi-parametric programming problem, with parameters being the (unknown) variables of the outer (leader's) problem. By inserting the obtained rational reaction sets in the upper level problem the overall problem is transformed into a set of independent quadratic, linear or mixed integer linear programming problems, which can be solved to global optimality. In particular, we solve bilevel quadratic and bilevel mixed integer linear problems, with or without right-hand-side uncertainty. A number of examples are presented to illustrate the steps and details of the proposed global optimisation strategy.
机译:我们基于最近开发的参数化编程算法,提出了一种用于解决各种类别的双层编程问题(BLPP)的全局优化方法。我们首先描述如何重铸和解决双层规划的内部(跟随者)问题,将其作为多参数编程问题,其中参数是外部(领导者)问题的(未知)变量。通过将获得的有理反应集插入上层问题中,整个问题将转化为一组独立的二次,线性或混合整数线性规划问题,可以将其求解为全局最优性。特别是,我们解决了带有或不带有右侧不确定性的双级二次和双级混合整数线性问题。给出了许多示例来说明所建议的全局优化策略的步骤和细节。

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