Document Type

Conference Proceeding

Publisher

IEEE

Faculty

Faculty of Computing, Health and Science

School

School of Engineering and Mathematics

RAS ID

2509

Comments

This is an Author's Accepted Manuscript of: Tang, M., Eshraghian, K. , & Habibi, D. (2001). Knowledge-based genetic algorithm for layer assignment. Proceedings of 2001 Australian Computer Science Conference (pp. 184-190). Gold Coast, QLD. IEEE. Available here

© 2001 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Abstract

Layer assignment is an important post-layout optimization technique in very large scale integrated circuit (VLSI) layout automation. It re-assigns wire segments in a routing solution to appropriate layers to achieve certain optimization objectives. The paper focuses on investigating the layer assignment problem with application to via minimization, which is known to be NP-complete. A knowledge based genetic algorithm for the layer assignment problem is proposed, with the aim of utilizing domain specific knowledge to speed up the process of evolution and to improve the quality of solutions. Experimental results show that this knowledge based genetic algorithm can consistently produce the same or better results than a heuristic algorithm and a traditional genetic algorithm

DOI

10.1109/ACSC.2001.906641

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free_to_read

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Link to publisher version (DOI)

10.1109/ACSC.2001.906641