An Efficient Hybrid Evolution Strategy Algorithm with Direct Search Method for Global Optimization

Author(s):  
Noureddine Boukhari ◽  
Fatima Debbat ◽  
Nicolas Monmarché ◽  
Mohamed Slimane

The main purpose of this article is to demonstrate how evolution strategy optimizers can be improved by incorporating an efficient hybridization scheme with restart strategy in order to jump out of local solution regions. The authors propose a hybrid (μ, λ)ES-NM algorithm based on the Nelder-Mead (NM) simplex search method and evolution strategy algorithm (ES) for unconstrained optimization. At first, a modified NM, called Adaptive Nelder-Mead (ANM) is used that exhibits better properties than standard NM and self-adaptive evolution strategy algorithm is applied for better performance, in addition to a new contraction criterion is proposed in this work. (μ, λ)ES-NM is balancing between the global exploration of the evolution strategy algorithm and the deep exploitation of the Nelder-Mead method. The experiment results show the efficiency of the new algorithm and its ability to solve optimization problems in the performance of accuracy, robustness, and adaptability.

2014 ◽  
Vol 1065-1069 ◽  
pp. 3438-3441
Author(s):  
Guo Jun Li

Harmony search (HS) algorithm is a new population based algorithm, which imitates the phenomenon of musical improvisation process. Its own potential and shortage, one shortage is that it easily trapped into local optima. In this paper, a hybrid harmony search algorithm (HHS) is proposed based on the conception of swarm intelligence. HHS employed a local search method to replace the pitch adjusting operation, and designed an elitist preservation strategy to modify the selection operation. Experiment results demonstrated that the proposed method performs much better than the HS and its improved algorithms (IHS, GHS and NGHS).


Author(s):  
Rohit Kumar Singla ◽  
Ranjan Das ◽  
Arka Bhowmik ◽  
Ramjee Repaka

This work deals with the application of the Nelder-Mead simplex search method (SSM) to study a porous extended surface. At first, analytical expression for calculating the local temperature field has been derived using an implicit Runge-Kutta method. The heat transfer phenomenon is assumed to be governed by conductive, naturally convective and radiative heat transfer, whereas the diffusion of mass through the porous media is also taken into account. Then, using the SSM, critical parameters such as porosity, permeability, and thermal conductivities of the extended surface have been predicted for satisfying a prescribed temperature field. It is found that many alternative solutions can meet a given thermal requirement, which is proposed to offer the flexibility in selecting the material and regulating the thermal conditions. It is observed that the allowable error in the temperature measurement should be limited within 5%. It is also found that even with few temperature measurement points, very good reconstruction of the thermal field is possible using the SSM.


2013 ◽  
Vol 49 (7) ◽  
pp. 1029-1038 ◽  
Author(s):  
Ranjan Das ◽  
Ashis Mallick ◽  
K. T. Ooi

Author(s):  
Ashraf O. Nassef ◽  
Ayman M. Ashraf ◽  
Sayed M. Metwalli

Abstract In many years of industry, it is desirable to create geometric models of existing objects for which no such models are available. Reverse engineering transforms real parts into engineering models and concepts. This paper presents an approach for fitting three-dimensional prismatic features using real-coded genetic algorithms. The approach is compared with the Nelder Meade Simplex search method as a variant of the traditional direct search method. The results show the superiority of the real-coded genetic algorithms over the traditional direct search method with respect to accuracy. The paper also concerns with the minimization of the fitting time through minimizing the number of objective function evaluations. This is done by optimizing the genetic algorithms parameters such as the number of times for which the various cross-overs and mutations should be applied.


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