Automatically assigned DDC number: 006331

Manually assigned DDC number: 006331

Number of references: 4

Title: A Hybrid Genetic Algorithm For The Channel Routing Problem

Author:

Author:

Author:

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Subject: Nicole Gockel,Gregor Pudelko,Rolf Drechsler,Bernd Becker A Hybrid Genetic Algorithm For The Channel Routing Problem

Description: We present a Hybrid Genetic Algorithm (HGA) for the Channel Routing Problem (CRP). To do so we combine a Genetic Algorithm (GA) with domain specific knowledge, i.e. the genetic operators make use of the rip-up and reroute technique. Thereby the execution time of our method is faster than previously presented evolutionary based approaches. Furthermore, concerning space complexity we show by experiments that our HGA can handle large channels (with more than 100 columns). 1. INTRODUCTION During the last years Genetic Algorithms (GAs) have become more and more popular in the domain of search, optimization and machine learning [6, 1]. In many areas they are superior to other classical optimization techniques, like e.g. gradient-descent. GAs have succesfully been applied to general hard problems [2] and recently are used for optimization in the area of Computer Aided Design (CAD), like placement, routing test pattern generation and logic synthesis (see e.g. [4, 3]). Often it is useful to ...

Contributor: The Pennsylvania State University CiteSeer Archives

Publisher: unknown

Date: 1998-09-04

Pubyear: 1996

Format: ps

Identifier: http://citeseer.ist.psu.edu/145254.html

Source: http://www.informatik.uni-freiburg.de/~drechsle/ps_test/CHANNEL.ps

Language: en

Relation:

Relation:

Relation:

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Rights: unrestricted

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