MODA元启发式:评价及在CCII规模中的应用

M. Kotti, Nizar Dhahri, M. Fakhfakh, B. Benhala
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引用次数: 0

摘要

本文研究了一种新的自然启发型多目标元启发式算法——多目标蜻蜓算法(MODA),并将其应用于模拟电路的优化设计。首先,通过不带/带约束的测试函数对MODA算法进行测试、验证,并与另一种元启发式算法进行比较。使用性能指标来显示对高度均匀分布的Pareto解的收敛精度。在第二部分中,使用该算法对模拟电路即第二代电流输送器的性能进行优化。将MODA的性能与使用MOPSO元启发式算法获得的性能进行比较,以显示所提算法的潜力。Spice仿真证明了MODA算法在模拟电路设计尺寸方面的优点。
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MODA metaheuristic: evaluation and application to CCII sizing
This paper presents a study and an adaptation of a new nature-inspired multi-objective metaheuristic algorithm, entitled the multi-objective Dragonfly Algorithm (MODA), to the optimal design of analog circuits. First, the MODA algorithm is tested, validated and compared to another metaheuristic algorithm thru test functions without/with constraints. Performance metrics are used to show the convergence accuracy to the Pareto solutions with highly uniform distribution. In the second part, the algorithm is used to optimize the performance of an analog circuit, namely a second-generation current conveyor. Comparison between MODA performances and those obtained using the MOPSO metaheuristic is provided to show potentialities of the proposed algorithm. Spice Simulations demonstrate the merits of the MODA algorithm in analog circuit design sizing.
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