Abstract

We present a new approach based on grammatical evolution (GE) aimed at addressing the analog electronic circuit design problem. In the new approach, called multi-grammatical evolution (MGE), a chromosome is a variable-length codon string that is divided into as many partitions as subproblems result from breaking down the original optimization problem: circuit topology and component sizing in our case. This leads to a modular approach where the solution of each subproblem is encoded and evolved in a partition of the chromosome. Additionally, each partition is decoded according to a specific grammar and the final solution to the original problem emerges as an aggregation result associated with the decoding process of the different partitions. Modularity facilitates the encoding and evolution of the solution in each subproblem. On the other way, homology helps to reduce the potentially destructive effect associated with standard crossover operators normally used in GE-based approaches. Seven analog circuit designs are addressed by an MGE-based method and the obtained results are compared to those obtained by different methods based on GE and other evolutionary paradigms. A simple parsimony mechanism was also introduced to ensure compliance with design specifications and reduce the number of components of the circuits obtained. We can conclude that our method obtains competitive results in the seven circuits analyzed.

Highlights

  • Analog death has been predicted so many times, but the analog integrated circuit (IC) market growth rate is currently even greater (6.6%) than the average rate for the whole IC market (5.1%) [1]

  • On, the implemented method based on multi-grammatical evolution (MGE) will be denoted by ACID-MGE, and the grammatical evolution (GE)-based method will be denoted by ACID-GE [62]

  • Each problem is decomposed into two levels of abstraction and each level is formalized by a specific grammar

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Summary

Introduction

Analog death has been predicted so many times, but the analog integrated circuit (IC) market growth rate is currently even greater (6.6%) than the average rate for the whole IC market (5.1%) [1]. Though there are powerful electronic design automation (EDA) tools which can almost fully automate the whole digital design process, this is not the case in analog design, where there is still no widely accepted tools [5]. Analog design is considered to be knowledge-intensive [4] and considerably more complex than digital design, even for small problem sizes [6]. Analog or mixed-signal designs typically need to optimize dozens of specifications, some of them conflicting, The associate editor coordinating the review of this manuscript and approving it for publication was Gustavo Olague. A single change could affect the whole design since analog circuits are bidirectional at their boundaries [8]. Most of the constraints in today’s analog design are still specified and considered manually by expert designers [6]

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