Continuous Optimization Algorithm for PCB Layout Based on Differential Evolution

In Printed Circuit Board (PCB) design, effective layout optimization is crucial for electrical performance, thermal management, and signal integrity. However, due to the inherently complex, high-dimensional nature of PCB layout problems, traditional optimization methods often struggle to deliver sat...

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Veröffentlicht in:2024 5th International Symposium on Computer Engineering and Intelligent Communications (ISCEIC) S. 253 - 259
Hauptverfasser: Wang, Yu, Chen, Tingting, Chen, Yu
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 08.11.2024
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Abstract In Printed Circuit Board (PCB) design, effective layout optimization is crucial for electrical performance, thermal management, and signal integrity. However, due to the inherently complex, high-dimensional nature of PCB layout problems, traditional optimization methods often struggle to deliver satisfactory solutions. This paper presents a continuous optimization algorithm for PCB layout based on Differential Evolution (DE). As a global search algorithm, DE effectively explores complex continuous optimization spaces through mutation operations based on the differences among individual solutions, enabling the identification of optimal layouts. We begin by formulating the PCB layout problem as a constrained multi-objective optimization issue. Subsequently, we enhance the DE algorithm's adaptability by introducing an adaptive mutation operator, which improves the balance between global search and local exploitation. To validate the effectiveness of the proposed algorithm, we conducted experiments using a series of real-world PCB design cases. The results demonstrate that the DE-based PCB layout optimization algorithm outperforms traditional methods across multiple performance metrics, particularly in high-dimensional complex scenarios, showcasing superior global optimization capabilities and convergence speed.
AbstractList In Printed Circuit Board (PCB) design, effective layout optimization is crucial for electrical performance, thermal management, and signal integrity. However, due to the inherently complex, high-dimensional nature of PCB layout problems, traditional optimization methods often struggle to deliver satisfactory solutions. This paper presents a continuous optimization algorithm for PCB layout based on Differential Evolution (DE). As a global search algorithm, DE effectively explores complex continuous optimization spaces through mutation operations based on the differences among individual solutions, enabling the identification of optimal layouts. We begin by formulating the PCB layout problem as a constrained multi-objective optimization issue. Subsequently, we enhance the DE algorithm's adaptability by introducing an adaptive mutation operator, which improves the balance between global search and local exploitation. To validate the effectiveness of the proposed algorithm, we conducted experiments using a series of real-world PCB design cases. The results demonstrate that the DE-based PCB layout optimization algorithm outperforms traditional methods across multiple performance metrics, particularly in high-dimensional complex scenarios, showcasing superior global optimization capabilities and convergence speed.
Author Wang, Yu
Chen, Tingting
Chen, Yu
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  surname: Chen
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  email: ychen@whut.edu.cn
  organization: Wuhan University of Technology,Wuhan,China
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Snippet In Printed Circuit Board (PCB) design, effective layout optimization is crucial for electrical performance, thermal management, and signal integrity. However,...
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StartPage 253
SubjectTerms Arithmetic
automatic PCB layout
Convergence
differential evolutionary arithmetic
electronic design automation
Evolutionary computation
Layout
Measurement
multi-objective optimization
Optimization
Optimization methods
Printed circuits
sequential optimization
Signal integrity
Thermal management
Title Continuous Optimization Algorithm for PCB Layout Based on Differential Evolution
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