Güner, Gürkan GüvenG. DemirciB. Altunoğlu2024-10-282022-01-01https://acikarsiv.thk.edu.tr/handle/123456789/2572There are many studies, which propose different heuristic and metaheuristic solution approaches for analog circuit design optimization, in the literature. Analog circuits have great design complexity in terms of circuit parameters, and each of the analog circuit designs has different limitations because of the various requirements. In general, analog circuit design steps are composed of choosing circuit structure, then optimizing the circuit parameters. Circuit parameters need to be designed for the output of the circuit such as power, noise, and gain. Due to the complexity and time-consuming factors for the circuit design, innovative and scientific solution approaches become important for the analog circuit design solution. This study focuses on the latest heuristic and metaheuristic solution approaches, such as the evolutionary algorithms including genetic algorithm and particle swarm optimization, for the analog circuit design considering different single-objective and multi-objective problems to show the future trends about the solution methodologies. The latest studies in the literature are classified according to their purposes, solution methodologies, and considered problems. It is intended that the comprehensive literature review in this study will be helpful for the decision-makers about suggesting a course of action for the latest trends in the optimal design of the analog circuits.Presentation