A numerical study of some modified differential evolution algorithms
نویسندگان
چکیده
Modifications in mutation and localization in acceptance rule are suggested to the differential evolution algorithm for global optimization. Numerical experiments indicate that the resulting algorithms are considerably better than the original differential evolution algorithm. Therefore, they offer a reasonable alternative to many currently available stochastic algorithms, especially for problems requiring _direct search type_ methods. Numerical study is carried out using a set of 50 test problems many of which are inspired by practical applications. © 2005 Elsevier B.V. All rights reserved.
منابع مشابه
Integrating Differential Evolution Algorithm with Modified Hybrid GA for Solving Nonlinear Optimal Control Problems
‎Here‎, ‎we give a two phases algorithm based on integrating differential evolution (DE) algorithm with modified hybrid genetic algorithm (MHGA) for solving the associated nonlinear programming problem of a nonlinear optimal control problem‎. ‎In the first phase‎, ‎DE starts with a completely random initial population where each individual‎, ‎or solution‎...
متن کاملMULTI-OBJECTIVE OPTIMIZATION OF ARCH DAMS USING DIFFERENTIAL EVOLUTION METHODS
For optimization of real-world arch dams, it is unavoidable to consider two or more conflicting objectives. This paper employs two multi-objective differential evolution algorithms (MoDE) in combination of a parallel working MATLAB-APDL code to obtain a set of Pareto solutions for optimal shape of arch dams. Full dam-reservoir interaction subjected to seismic loading is considered. A benchmark ...
متن کاملNumerical solution of a system of fuzzy polynomial equations by modified Adomian decomposition method
In this paper, we present some efficient numerical algorithm for solving system of fuzzy polynomial equations based on Newton's method. The modified Adomian decomposition method is applied to construct the numerical algorithms. Some numerical illustrations are given to show the efficiency of algorithms.
متن کاملWell Placement Optimization Using Differential Evolution Algorithm
Determining the optimal location of wells with the aid of an automated search algorithm is a significant and difficult step in the reservoir development process. It is a computationally intensive task due to the large number of simulation runs required. Therefore,the key issue to such automatic optimization is development of algorithms that can find acceptable solutions with a minimum numbe...
متن کاملA Differential Evolution and Spatial Distribution based Local Search for Training Fuzzy Wavelet Neural Network
Abstract Many parameter-tuning algorithms have been proposed for training Fuzzy Wavelet Neural Networks (FWNNs). Absence of appropriate structure, convergence to local optima and low speed in learning algorithms are deficiencies of FWNNs in previous studies. In this paper, a Memetic Algorithm (MA) is introduced to train FWNN for addressing aforementioned learning lacks. Differential Evolution...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- European Journal of Operational Research
دوره 169 شماره
صفحات -
تاریخ انتشار 2006