{"title":"模拟电路设计优化的元启发式研究综述","authors":"Abdelaziz Lberni , Malika Alami Marktani , Abdelaziz Ahaitouf , Ali Ahaitouf","doi":"10.1016/j.swevo.2025.102170","DOIUrl":null,"url":null,"abstract":"<div><div>As CMOS technology continues to scale down, the design complexity of very large-scale integrated circuits (VLSI) is rapidly increasing. Analog circuit design, in particular, remains time-consuming due to the critical impact of component dimensions on performance. Although the application of metaheuristics in analog circuit automation dates back to the 1980s, the growing complexity of analog design tasks and the need to reduce design cycles has sparked renewed interest in using metaheuristic approaches to address these challenges. In this paper, we provide a comprehensive and up-to-date review of existing studies on the application of metaheuristics in analog circuit design automation, including circuit synthesis, sizing, and layout synthesis, while assessing their effectiveness in meeting design objectives. The paper provides an in-depth discussion from the metaheuristics perspective and highlights key research directions for future exploration.</div></div>","PeriodicalId":48682,"journal":{"name":"Swarm and Evolutionary Computation","volume":"99 ","pages":"Article 102170"},"PeriodicalIF":8.5000,"publicationDate":"2025-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Metaheuristics for analog circuit design optimization: A survey\",\"authors\":\"Abdelaziz Lberni , Malika Alami Marktani , Abdelaziz Ahaitouf , Ali Ahaitouf\",\"doi\":\"10.1016/j.swevo.2025.102170\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>As CMOS technology continues to scale down, the design complexity of very large-scale integrated circuits (VLSI) is rapidly increasing. Analog circuit design, in particular, remains time-consuming due to the critical impact of component dimensions on performance. Although the application of metaheuristics in analog circuit automation dates back to the 1980s, the growing complexity of analog design tasks and the need to reduce design cycles has sparked renewed interest in using metaheuristic approaches to address these challenges. In this paper, we provide a comprehensive and up-to-date review of existing studies on the application of metaheuristics in analog circuit design automation, including circuit synthesis, sizing, and layout synthesis, while assessing their effectiveness in meeting design objectives. The paper provides an in-depth discussion from the metaheuristics perspective and highlights key research directions for future exploration.</div></div>\",\"PeriodicalId\":48682,\"journal\":{\"name\":\"Swarm and Evolutionary Computation\",\"volume\":\"99 \",\"pages\":\"Article 102170\"},\"PeriodicalIF\":8.5000,\"publicationDate\":\"2025-09-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Swarm and Evolutionary Computation\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S221065022500327X\",\"RegionNum\":1,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Swarm and Evolutionary Computation","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S221065022500327X","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
Metaheuristics for analog circuit design optimization: A survey
As CMOS technology continues to scale down, the design complexity of very large-scale integrated circuits (VLSI) is rapidly increasing. Analog circuit design, in particular, remains time-consuming due to the critical impact of component dimensions on performance. Although the application of metaheuristics in analog circuit automation dates back to the 1980s, the growing complexity of analog design tasks and the need to reduce design cycles has sparked renewed interest in using metaheuristic approaches to address these challenges. In this paper, we provide a comprehensive and up-to-date review of existing studies on the application of metaheuristics in analog circuit design automation, including circuit synthesis, sizing, and layout synthesis, while assessing their effectiveness in meeting design objectives. The paper provides an in-depth discussion from the metaheuristics perspective and highlights key research directions for future exploration.
期刊介绍:
Swarm and Evolutionary Computation is a pioneering peer-reviewed journal focused on the latest research and advancements in nature-inspired intelligent computation using swarm and evolutionary algorithms. It covers theoretical, experimental, and practical aspects of these paradigms and their hybrids, promoting interdisciplinary research. The journal prioritizes the publication of high-quality, original articles that push the boundaries of evolutionary computation and swarm intelligence. Additionally, it welcomes survey papers on current topics and novel applications. Topics of interest include but are not limited to: Genetic Algorithms, and Genetic Programming, Evolution Strategies, and Evolutionary Programming, Differential Evolution, Artificial Immune Systems, Particle Swarms, Ant Colony, Bacterial Foraging, Artificial Bees, Fireflies Algorithm, Harmony Search, Artificial Life, Digital Organisms, Estimation of Distribution Algorithms, Stochastic Diffusion Search, Quantum Computing, Nano Computing, Membrane Computing, Human-centric Computing, Hybridization of Algorithms, Memetic Computing, Autonomic Computing, Self-organizing systems, Combinatorial, Discrete, Binary, Constrained, Multi-objective, Multi-modal, Dynamic, and Large-scale Optimization.