A hybrid genetic algorithm and application to the crosstalk aware track assignment problem

Authors:
Yici Cai;Bin Liu;Xiong Yan;Qiang Zhou;Xianlong Hong
Affiliations:
Department of Computer Science, University of Science and Technology of China, Hefei, China;Department of Computer Science and Technology, Tsinghua University, Beijing, China;Department of Computer Science, University of Science and Technology of China, Hefei, China;Department of Computer Science and Technology, Tsinghua University, Beijing, China;Department of Computer Science and Technology, Tsinghua University, Beijing, China
Venue:
ICNC'05 Proceedings of the First international conference on Advances in Natural Computation - Volume Part III
Year:
2005

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Abstract

This paper presents a genetic algorithm hybridized with a constructive procedure and reports its application on the crosstalk aware track assignment problem. In this algorithm, only dominating elements are encoded as chromosomes, on which genetic operators work to explore the solution space, while other elements are determined using constructive method. With proper dominating elements identification, the proposed approach essentially searches a much smaller space without trivial operations, efficiently generating competitive solutions with an effective constructive procedure. Experimental results on a set of industrial instances and ISPD98 benchmarks show that the proposed algorithm reduces both capacitive and inductive coupling in acceptable running time. It is probable that the proposed approach provides a practical way for the application of genetic algorithm on large scale engineering problems.