A Local Search Heuristic for Biobjective Intersecting Geometric Graphs

Rajeev Kumar, P. Singh, B. Bhattacharya
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引用次数: 0

Abstract

In this work, we consider the problem of constructing spanning trees from two geometric graphs corresponding to two nets, each with multiple terminals, with a goal to minimize the total edge cost and the number of intersections among the edges of the two trees. Such an optimization problem is computationally hard for which no efficient algorithm or good heuristic is known to exist. Additionally, in a biobjective setting, the major challenge to solve a problem is to obtain many representative diverse solutions across the (near-) optimal Pareto-front. We present a local search based heuristic to find near-optimal Pareto-front in the feasible solution space. Each element of this solution set is a tuple of two spanning trees corresponding to the given geometric graphs. The heuristic is shown to give superior results over the existing stochastic technique
双目标相交几何图的局部搜索启发式算法
在这项工作中,我们考虑了从对应于两个网络的两个几何图构建生成树的问题,每个网络都有多个终端,目标是最小化总边缘成本和两棵树边缘之间的相交数量。这种优化问题在计算上是困难的,没有有效的算法或好的启发式已知存在。此外,在双目标设置中,解决问题的主要挑战是在(接近)最优Pareto-front中获得许多具有代表性的不同解。提出了一种基于局部搜索的启发式算法,用于在可行解空间中寻找近最优Pareto-front。这个解集的每个元素是由两个生成树组成的元组,对应于给定的几何图。与现有的随机方法相比,启发式方法具有更好的效果
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