Manifold block optimization method by utilizing evolution algorithm

2009 ◽  
Author(s):  
Jingben Yin ◽  
Lei Zhao ◽  
Juntao Wang
Keyword(s):  
Optimization Method ◽  
Evolution Algorithm

scholarly journals Cloud Particles Differential Evolution Algorithm: A Novel Optimization Method for Global Numerical Optimization

2015 ◽  
Vol 2015 ◽  
pp. 1-36 ◽  
Author(s):  
Wei Li ◽  
Lei Wang ◽  
Quanzhu Yao ◽  
Qiaoyong Jiang ◽  
Lei Yu ◽  
...  
Keyword(s):  
Solid State ◽  
Differential Evolution ◽  
Liquid State ◽  
Differential Evolution Algorithm ◽  
Optimization Method ◽  
Benchmark Problems ◽  
Gaseous State ◽  
Mutation Strategy ◽  
Evolution Algorithm ◽  
Cloud Particles

We propose a new optimization algorithm inspired by the formation and change of the cloud in nature, referred to as Cloud Particles Differential Evolution (CPDE) algorithm. The cloud is assumed to have three states in the proposed algorithm. Gaseous state represents the global exploration. Liquid state represents the intermediate process from the global exploration to the local exploitation. Solid state represents the local exploitation. The best solution found so far acts as a nucleus. In gaseous state, the nucleus leads the population to explore by condensation operation. In liquid state, cloud particles carry out macrolocal exploitation by liquefaction operation. A new mutation strategy called cloud differential mutation is introduced in order to solve a problem that the misleading effect of a nucleus may cause the premature convergence. In solid state, cloud particles carry out microlocal exploitation by solidification operation. The effectiveness of the algorithm is validated upon different benchmark problems. The results have been compared with eight well-known optimization algorithms. The statistical analysis on performance evaluation of the different algorithms on 10 benchmark functions and CEC2013 problems indicates that CPDE attains good performance.

Multi-Agent Order Selection and its Optimization Method with Evolution Algorithm

2010 ◽  
Vol 20-23 ◽  
pp. 1066-1071
Author(s):  
Li Zhang ◽  
Jie Wu Zhang ◽  
Wei Jun Ma
Keyword(s):  
Optimization Algorithm ◽  
Model Simulation ◽  
Optimization Method ◽  
Business Environment ◽  
Autonomous Agent ◽  
Fast Time ◽  
Architecture Model ◽  
Rapid Changes ◽  
Multi Agent ◽  
Evolution Algorithm

The rapid changes of market and outer surroundings have caused a dynamic and highly volatile business environment for the enterprise. Manufacturing organizations are seeking efficiency gains by competing via fast time-to-market and low production cost. An Autonomous Agent Network(ANN) Based Manufacturing System model is introduced, as well as the mathematics expression for the components of AAN model. The optimization algorithm based on evolution algorithm is used to solve the optimization problem of the model. Simulation results show that the architecture model and its optimization algorithm are effective to the problem.

Optimization of FLADE Variable Cycle Engine Performance Based on Improved Differential Evolution Algorithm

2017 ◽  
Author(s):  
Zhang Xiao-bo ◽  
Wang Zhan-xue
Keyword(s):  
Differential Evolution ◽  
Differential Evolution Algorithm ◽  
Engine Performance ◽  
Optimization Method ◽  
Performance Simulation ◽  
De Algorithm ◽  
Civil Aircraft ◽  
Evolution Algorithm ◽  
Improved Differential Evolution Algorithm ◽  
Integrated Performance

In this paper, a double bypass variable cycle engine with FLADE (Fan on Blade) is considered. The FLADE VCE is one of the research hotspots for future military and civil aircraft power device, which shows outstanding performance advantages. Compared to the mixed-flow turbofan, FLADE VCE is more complex than conventional aero-engine for its multi-components and multi-variable parts, which make it difficult to modeling and optimization. For getting the performance of FLADE VCE, the model for engine performance simulation is researched. The method for FLADE performance simulation and the steady-state performance simulation model for FLADE VCE are developed. And a component-based engine performance simulation system is established based on object-oriented modeling method. For obtaining the optimal integrated performance of FLADE VCE, suitable optimization method is required. Unfortunately, the optimization of FLADE VCE is a non-linear non-differentiable problem, which makes it difficult to solve by conventional deterministic optimization method. In order to solve this problem, the differential evolution (DE) algorithm is considered. To overcome the limitations of original DE algorithm, an improved DE algorithm with modifying mutation operator is proposed by this paper. The FLADE VCE optimization problem is solved by employing the improved DE algorithm.

scholarly journals What are grain boundary structures in graphene?

Nanoscale ◽  
2014 ◽  
Vol 6 (8) ◽  
pp. 4309-4315 ◽  
Author(s):  
Zheng-Lu Li ◽  
Zhi-Ming Li ◽  
Hai-Yuan Cao ◽  
Ji-Hui Yang ◽  
Qiang Shu ◽  
...  
Keyword(s):  
Global Optimization ◽  
Grain Boundary ◽  
Differential Evolution ◽  
Differential Evolution Algorithm ◽  
Optimization Method ◽  
Interface Structure ◽  
Global Optimization Method ◽  
Evolution Algorithm

We have developed a new global optimization method for the determination of the interface structure based on the differential evolution algorithm.

Modified Harmony Search Algorithm for Unconstrained Numerical Optimization Problems

2014 ◽  
Vol 989-994 ◽  
pp. 2528-2531
Author(s):  
Hong Gang Xia ◽  
Qing Zhou Wang
Keyword(s):  
Numerical Optimization ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Harmony Search ◽  
Differential Evolution Algorithm ◽  
Optimization Method ◽  
Harmony Search Algorithm ◽  
Local Optimum ◽  
Perfect State ◽  
Evolution Algorithm

Harmony search algorithm is a new meta-heuristic optimization method imitating the music improvisation process where musicians improvise their instruments’ pitches searching for a perfect state of harmony. To enable the harmony search algorithm to transcend its limited capability of local optimum, a modified harmony search algorithm is proposed in this paper. In the modified harmony search algorithm, the mutation operation of differential evolution algorithm is introduced into MHS algorithm, which improves its convergence. Several standard benchmark optimization functions are to be test and compare the performance of the MHS. The results revealed the superiority of the proposed method to the HS and recently developed variants.

scholarly journals A heuristic optimization method of fractional convection reaction: An application to diffusion process

2018 ◽  
Vol 22 (Suppl. 1) ◽  
pp. 243-252 ◽  
Author(s):  
Najeeb Khan ◽  
Tooba Hameed ◽  
Nadeem Khan ◽  
Muhammad Raja
Keyword(s):  
Diffusion Process ◽  
Differential Evolution ◽  
Optimization Technique ◽  
Differential Evolution Algorithm ◽  
Optimization Method ◽  
Heuristic Optimization ◽  
Rapid Convergence ◽  
Convection Diffusion ◽  
Fractional Differential ◽  
Evolution Algorithm

The convection differential models play an essential role in studying different chemical process and effects of the diffusion process. This paper intends to provide optimized numerical results of such equations based on the conformable fractional derivative. Subsequently, a well-known heuristic optimization technique, differential evolution algorithm, is worked out together with the Taylor?s series expansion, to attain the optimized results. In the scheme of the Taylor optimization method (TOM), after expanding the functions with the Taylor?s series, the unknown terms of the series are then globally optimized using differential evolution. Moreover, to illustrate the applicability of TOM, some examples of linear and non-linear fractional convection diffusion equations are exemplified graphically. The obtained assessments and comparative demonstrations divulged the rapid convergence of the estimated solutions towards the exact solutions. Comprising with an effective expander and efficient optimizer, TOM reveals to be an appropriate approach to solve different fractional differential equations modeling various problems of engineering.

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