PCB layout design using a genetic algorithm

Sakait Jain, Hae Chang Gea

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

This paper presents an approach to find the optimal design layout of chips on a circuit board in a manner that minimizes the area covered on the board and the connections between the various chips. In addition, there are no major heat sources next to each other and certain physical constraints are satisfied while finding a layout design. In this approach, the whole circuit board area is divided into a finite number of cells for mapping it into a genetic algorithm chromosome. The mutation and crossover operators have been modified and are applied in conjunction with connectivity analysis for the chips to reduce the creation of a lot of faulty generations. Examples of GA based chip layout are presented to show how each of the objectives are attained separately followed by examples to arrive at layouts using multiple objectives.

Original languageEnglish (US)
Title of host publication21st Design Automation Conference
PublisherAmerican Society of Mechanical Engineers (ASME)
Pages529-536
Number of pages8
ISBN (Electronic)9780791817162
DOIs
StatePublished - 1995
EventASME 1995 Design Engineering Technical Conferences, DETC 1995, collocated with the ASME 1995 15th International Computers in Engineering Conference and the ASME 1995 9th Annual Engineering Database Symposium - Boston, United States
Duration: Sep 17 1995Sep 20 1995

Publication series

NameProceedings of the ASME Design Engineering Technical Conference
Volume1

Conference

ConferenceASME 1995 Design Engineering Technical Conferences, DETC 1995, collocated with the ASME 1995 15th International Computers in Engineering Conference and the ASME 1995 9th Annual Engineering Database Symposium
Country/TerritoryUnited States
CityBoston
Period9/17/959/20/95

All Science Journal Classification (ASJC) codes

  • Mechanical Engineering
  • Computer Graphics and Computer-Aided Design
  • Computer Science Applications
  • Modeling and Simulation

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