Simple alternating path problem
Discrete Mathematics
Intersection number of two connected geometric graphs
Information Processing Letters
Bicriteria network design problems
Journal of Algorithms
Genetic algorithms for VLSI design, layout & test automation
Genetic algorithms for VLSI design, layout & test automation
When crossings count — approximating the minimum spanning tree
Proceedings of the sixteenth annual symposium on Computational geometry
Algorithms for VLSI Physcial Design Automation
Algorithms for VLSI Physcial Design Automation
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Introduction to Algorithms
Bipartite Embeddings of Trees in the Plane
GD '96 Proceedings of the Symposium on Graph Drawing
Proceedings of the 2003 ACM symposium on Applied computing
On plane spanning trees and cycles of multicolored point sets with few intersections
Information Processing Letters
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
A new evolutionary approach to the degree-constrained minimumspanning tree problem
IEEE Transactions on Evolutionary Computation
Performance assessment of multiobjective optimizers: an analysis and review
IEEE Transactions on Evolutionary Computation
Edge sets: an effective evolutionary coding of spanning trees
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
| Hi-index | 0.00 |
Wire routing in a VLSI chip often requires minimization of ire-length as well as the number of intersections among multiple nets. 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 representative diverse solutions across the (near-) Pareto-front.In this work, we consider the problem of constructing spanning trees of 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. We first design simple heuristics to obtain the extreme points in the solution space, which however, could not produce diverse solutions. Search algorithms based on evolutionary multiobjective optimization (EMO) are then proposed to obtain diverse solutions in the feasible solution space. Each element of this solution set is a tuple of two spanning trees corresponding to the given geometric graphs. Empirical evidence shows that the proposed evolutionary algorithms cover a larger range and are much superior to the heuristics.