Global Optimization by Differential Evolution and Particle Swarm Methods: Evaluation on Some Benchmark Functions
نویسندگان
چکیده
منابع مشابه
Global Optimization by Differential Evolution and Particle Swarm Methods Evaluation on Some Benchmark Functions
I. A Brief History of Optimization Research: The history of optimization of realvalued non-linear functions (including linear ones), unconstrained or constrained, goes back to Gottfried Leibniz, Isaac Newton, Leonhard Euler and Joseph Lagrange. However, those mathematicians often assumed differentiability of the optimand as well as constraint functions. Moreover, they often dealt with the equal...
متن کاملAn Adaptive Hybrid Algorithm Based on Particle Swarm Optimization and Differential Evolution for Global Optimization
Particle swarm optimization (PSO) and differential evolution (DE) are both efficient and powerful population-based stochastic search techniques for solving optimization problems, which have been widely applied in many scientific and engineering fields. Unfortunately, both of them can easily fly into local optima and lack the ability of jumping out of local optima. A novel adaptive hybrid algori...
متن کاملglobal results on some nonlinear partial differential equations for direct and inverse problems
در این رساله به بررسی رفتار جواب های رده ای از معادلات دیفرانسیل با مشتقات جزیی در دامنه های کراندار می پردازیم . این معادلات به فرم نیم-خطی و غیر خطی برای مسایل مستقیم و معکوس مورد مطالعه قرار می گیرند . به ویژه، تاثیر شرایط مختلف فیزیکی را در مساله، نظیر وجود موانع و منابع، پراکندگی و چسبندگی در معادلات موج و گرما بررسی می کنیم و به دنبال شرایطی می گردیم که متضمن وجود سراسری یا عدم وجود سراسر...
Particle Swarm Optimization and Differential Evolution Methods Hybridized with Pattern Search for Solving Optimization Problems
Derivative-free methods are being explored recently due to the increased complexity of the models used in the optimization problems, and the impossibility/inconvenience of using derivatives in several situations. However, those methods show some limitations due to their low convergence rate, and when the problem is high-dimensional. Metaheuristics are another commonly adopted type of search tec...
متن کاملGaussian Particle Swarm Optimization with Differential Evolution Mutation
During the past decade, the particle swarm optimization (PSO) with various versions showed competitiveness on the constrained optimization problems. In this paper, an improved Gaussian particle swarm optimization algorithm (GPSO) is proposed to improve the diversity and local search ability of the population. A mutation operator based on differential evolution (DE) is designed and employed to u...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: SSRN Electronic Journal
سال: 2006
ISSN: 1556-5068
DOI: 10.2139/ssrn.933827