Cartesian Genetic Programming with a Modified Selection Operator for Combinational Circuit Design: Arithmetic Multipliers and Adders

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F26%3A0201220" target="_blank" >RIV/00216305:26220/26:0201220 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-031-84356-3_5" target="_blank" >http://dx.doi.org/10.1007/978-3-031-84356-3_5</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-031-84356-3_5" target="_blank" >10.1007/978-3-031-84356-3_5</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Cartesian Genetic Programming with a Modified Selection Operator for Combinational Circuit Design: Arithmetic Multipliers and Adders

Popis výsledku v původním jazyce

The evolutionary design of combinational logic circuits offers an innovative approach that often surpasses traditional methods, such as the Quine-McCluskey algorithm, in both efficiency and effectiveness. Cartesian Genetic Programming (CGP) emerges as a potent technique in this domain, enabling versatile circuit designs tailored to diverse requirements such as cost, gate count, and circuit speed. In this paper, we introduce an advanced modification of CGP, termed CGP-SA, which integrates the Simulated Annealing mechanism into the selection operator. This novel approach enhances the algorithm's ability to escape local optima, thereby fostering the discovery of more optimal solutions. We demonstrate the efficacy of CGP-SA through the design of three types of multipliers and two types of adders, utilizing diverse logic gate sets. This exploration not only reveals the flexibility of CGP-SA in handling various circuit design challenges but also highlights its adaptability to different optimization criteria.

Název v anglickém jazyce

Cartesian Genetic Programming with a Modified Selection Operator for Combinational Circuit Design: Arithmetic Multipliers and Adders

Popis výsledku anglicky

The evolutionary design of combinational logic circuits offers an innovative approach that often surpasses traditional methods, such as the Quine-McCluskey algorithm, in both efficiency and effectiveness. Cartesian Genetic Programming (CGP) emerges as a potent technique in this domain, enabling versatile circuit designs tailored to diverse requirements such as cost, gate count, and circuit speed. In this paper, we introduce an advanced modification of CGP, termed CGP-SA, which integrates the Simulated Annealing mechanism into the selection operator. This novel approach enhances the algorithm's ability to escape local optima, thereby fostering the discovery of more optimal solutions. We demonstrate the efficacy of CGP-SA through the design of three types of multipliers and two types of adders, utilizing diverse logic gate sets. This exploration not only reveals the flexibility of CGP-SA in handling various circuit design challenges but also highlights its adaptability to different optimization criteria.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

20205 - Automation and control systems

Projekt

<a href="/cs/project/GA24-12474S" target="_blank" >GA24-12474S: Benchmarking globálních optimalizačních metod</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Lecture Notes in Artificial Intelligence

ISBN

978-3-031-84355-6

ISSN

—

e-ISSN

1611-3349

Počet stran výsledku

13

Strana od-do

53-65

Název nakladatele

Springer Nature

Místo vydání

CHAM

Místo konání akce

Zakopane, Poland

Datum konání akce

16. 6. 2024

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

001535049000005