LSHADE with semi-parameter adaptation hybrid with CMA-ES for solving CEC 2017 benchmark problems

2017 ◽  
Author(s):  
Ali W. Mohamed ◽  
Anas A. Hadi ◽  
Anas M. Fattouh ◽  
Kamal M. Jambi
Keyword(s):  
Benchmark Problems ◽  
Parameter Adaptation

scholarly journals Differential Evolution with Population and Strategy Parameter Adaptation

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
V. Gonuguntla ◽  
R. Mallipeddi ◽  
Kalyana C. Veluvolu
Keyword(s):  
Differential Evolution ◽  
Population Size ◽  
Optimization Problems ◽  
Search Space ◽  
Benchmark Problems ◽  
Parameter Adaptation ◽  
De Algorithm ◽  
Probabilistic Technique ◽  
Number Of Individuals ◽  
Strategy Parameters

Differential evolution (DE) is simple and effective in solving numerous real-world global optimization problems. However, its effectiveness critically depends on the appropriate setting of population size and strategy parameters. Therefore, to obtain optimal performance the time-consuming preliminary tuning of parameters is needed. Recently, different strategy parameter adaptation techniques, which can automatically update the parameters to appropriate values to suit the characteristics of optimization problems, have been proposed. However, most of the works do not control the adaptation of the population size. In addition, they try to adapt each strategy parameters individually but do not take into account the interaction between the parameters that are being adapted. In this paper, we introduce a DE algorithm where both strategy parameters are self-adapted taking into account the parameter dependencies by means of a multivariate probabilistic technique based on Gaussian Adaptation working on the parameter space. In addition, the proposed DE algorithm starts by sampling a huge number of sample solutions in the search space and in each generation a constant number of individuals from huge sample set are adaptively selected to form the population that evolves. The proposed algorithm is evaluated on 14 benchmark problems of CEC 2005 with different dimensionality.

Fuzzy Based Parameter Adaptation in ACO for Solving VRP

2019 ◽  
Vol 10 (2) ◽  
pp. 65-81 ◽  
Author(s):  
Sandhya ◽  
Rajiv Goel
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Control Mechanism ◽  
Optimization Problems ◽  
Adaptive Strategies ◽  
Benchmark Problems ◽  
Parameter Control ◽  
Computational Results ◽  
Parameter Adaptation ◽  
Routing Problem

Ant Colony Optimization, a popular class of metaheuristics, have been widely applied for solving optimization problems like Vehicle Routing Problem. The performance of ACO is affected by the values of parameters used. However, in literature, few methods are proposed for parameter adaptation of ACO. In this article, a fuzzy-based parameter control mechanism for ACO has been developed. Three adaptive strategies FACO-1, FACO-2, FACO-3 are proposed for determining values of parameters alpha and beta, and evaporation factor separately as well as for all three parameters simultaneously. The performance of proposed strategies is compared with standard ACS on TSP and VRP benchmarks. Computational results on standard benchmark problems shows the effectiveness of the strategies.

scholarly journals Differential Evolution with Shadowed and General Type-2 Fuzzy Systems for Dynamic Parameter Adaptation in Optimal Design of Fuzzy Controllers

Axioms ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 194
Author(s):  
Patricia Ochoa ◽  
Oscar Castillo ◽  
Patricia Melin ◽  
José Soria
Keyword(s):  
Differential Evolution ◽  
Fuzzy Systems ◽  
General Type ◽  
Differential Evolution Algorithm ◽  
Dynamic Parameter ◽  
Benchmark Problems ◽  
Parameter Adaptation ◽  
Different Types ◽  
Evolution Algorithm

This work is mainly focused on improving the differential evolution algorithm with the utilization of shadowed and general type 2 fuzzy systems to dynamically adapt one of the parameters of the evolutionary method. Previously, we have worked with both kinds of fuzzy systems in different types of benchmark problems and it has been found that the use of fuzzy logic in combination with the differential evolution algorithm gives good results. In some of the studies, it is clearly shown that, when compared to other algorithms, our methodology turns out to be statistically better. In this case, the mutation parameter is dynamically moved during the evolution process by using shadowed and general type-2 fuzzy systems. The main contribution of this work is the ability to determine, through experimentation in a benchmark control problem, which of the two kinds of the used fuzzy systems has better results when combined with the differential evolution algorithm. This is because there are no similar works to our proposal in which shadowed and general type 2 fuzzy systems are used and compared. Moreover, to validate the performance of both fuzzy systems, a noise level is used in the controller, which simulates the disturbances that may exist in the real world and is thus able to validate statistically if there are significant differences between shadowed and general type 2 fuzzy systems.

An Eight-Node Hexahedral Finite Element with Rotational DOFs for Elastoplastic Applications

2019 ◽  
Vol 11 (1) ◽  
pp. 54-66
Author(s):  
Ayoub Ayadi ◽  
Kamel Meftah ◽  
Lakhdar Sedira ◽  
Hossam Djahara
Keyword(s):  
Mathematical Model ◽  
Finite Element ◽  
Plastic Zone ◽  
Displacement Vector ◽  
Small Strain ◽  
Benchmark Problems ◽  
Plasticity Model ◽  
Vector Approximation ◽  
Calculation Code

Abstract In this paper, the earlier formulation of the eight-node hexahedral SFR8 element is extended in order to analyze material nonlinearities. This element stems from the so-called Space Fiber Rotation (SFR) concept which considers virtual rotations of a nodal fiber within the element that enhances the displacement vector approximation. The resulting mathematical model of the proposed SFR8 element and the classical associative plasticity model are implemented into a Fortran calculation code to account for small strain elastoplastic problems. The performance of this element is assessed by means of a set of nonlinear benchmark problems in which the development of the plastic zone has been investigated. The accuracy of the obtained results is principally evaluated with some reference solutions.

Model Order Reduction of Transmission Line Model

2020 ◽  
Vol 19 ◽  
Keyword(s):  
Transmission Line ◽  
Large Scale ◽  
Original System ◽  
Reduced Order Model ◽  
Benchmark Problems ◽  
Transmission Line Model ◽  
Order Model ◽  
Line Model ◽  
Reduced Order ◽  
Numerical Effort

Transmission Line model are an important role in the electrical power supply. Modeling of such system remains a challenge for simulations are necessary for designing and controlling modern power systems.In order to analyze the numerical approach for a benchmark collection Comprehensive of some needful real-world examples, which can be utilized to evaluate and compare mathematical approaches for model reduction. The approach is based on retaining the dominant modes of the system and truncation comparatively the less significant once.as the reduced order model has been derived from retaining the dominate modes of the large-scale stable system, the reduction preserves the stability. The strong demerit of the many MOR methods is that, the steady state values of the reduced order model does not match with the higher order systems. This drawback has been try to eliminated through the Different MOR method using sssMOR tools. This makes it possible for a new assessment of the error system Offered that the Observability Gramian of the original system has as soon as been thought about, an H∞ and H2 error bound can be calculated with minimal numerical effort for any minimized model attributable to The reduced order model (ROM) of a large-scale dynamical system is essential to effortlessness the study of the system utilizing approximation Algorithms. The response evaluation is considered in terms of response constraints and graphical assessments. the application of Approximation methods is offered for arising ROM of the large-scale LTI systems which consist of benchmark problems. The time response of approximated system, assessed by the proposed method, is also shown which is excellent matching of the response of original system when compared to the response of other existing approaches .

scholarly journals Internal Leakage Fault Detection and Tolerant Control of Single-Rod Hydraulic Actuators

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Jianyong Yao ◽  
Guichao Yang ◽  
Dawei Ma
Keyword(s):  
Fault Detection ◽  
Simple Structure ◽  
Control Method ◽  
Fault Tolerant ◽  
Parameter Adaptation ◽  
Servo Systems ◽  
Hydraulic Actuators ◽  
Quadratic Lyapunov Functions ◽  
Safety And Reliability ◽  
Hydraulic Servo

The integration of internal leakage fault detection and tolerant control for single-rod hydraulic actuators is present in this paper. Fault detection is a potential technique to provide efficient condition monitoring and/or preventive maintenance, and fault tolerant control is a critical method to improve the safety and reliability of hydraulic servo systems. Based on quadratic Lyapunov functions, a performance-oriented fault detection method is proposed, which has a simple structure and is prone to implement in practice. The main feature is that, when a prescribed performance index is satisfied (even a slight fault has occurred), there is no fault alarmed; otherwise (i.e., a severe fault has occurred), the fault is detected and then a fault tolerant controller is activated. The proposed tolerant controller, which is based on the parameter adaptive methodology, is also prone to realize, and the learning mechanism is simple since only the internal leakage is considered in parameter adaptation and thus the persistent exciting (PE) condition is easily satisfied. After the activation of the fault tolerant controller, the control performance is gradually recovered. Simulation results on a hydraulic servo system with both abrupt and incipient internal leakage fault demonstrate the effectiveness of the proposed fault detection and tolerant control method.

Buckling characteristics of cut-out borne composite stiffened hyperbolic paraboloid shell panel

2021 ◽  
pp. 146442072110058
Author(s):  
Sarmila Sahoo
Keyword(s):  
Finite Element ◽  
Orientation Angle ◽  
Buckling Load ◽  
Benchmark Problems ◽  
Hyperbolic Paraboloid ◽  
Element Analysis ◽  
Load Effect ◽  
Global Buckling ◽  
Fiber Orientation Angle ◽  
Shell Panel

The present study investigates buckling characteristics of cut-out borne stiffened hyperbolic paraboloid shell panel made of laminated composites using finite element analysis to evaluate the governing differential equations of global buckling of the structure. The finite element code is validated by solving benchmark problems from literature. Different parametric variations are studied to find the optimum panel buckling load. Laminations, boundary conditions, depth of stiffener and arrangement of stiffeners are found to influence the panel buckling load. Effect of different parameters like cut-out size, shell width to thickness ratio, degree of orthotropy and fiber orientation angle of the composite layers on buckling load are also studied. Parametric and comparative studies are conducted to analyze the buckling strength of composite hyperbolic paraboloid shell panel with cut-out.

scholarly journals Particle Swarm Optimization Combined with Inertia-Free Velocity and Direction Search

Electronics ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 597
Author(s):  
Kun Miao ◽  
Qian Feng ◽  
Wei Kuang
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm ◽  
Optimal Solution ◽  
Small Region ◽  
Benchmark Problems ◽  
Swarm Optimization ◽  
Local Searches ◽  
Engineering Design Problems ◽  
Direction Search

The particle swarm optimization algorithm (PSO) is a widely used swarm-based natural inspired optimization algorithm. However, it suffers search stagnation from being trapped into a sub-optimal solution in an optimization problem. This paper proposes a novel hybrid algorithm (SDPSO) to improve its performance on local searches. The algorithm merges two strategies, the static exploitation (SE, a velocity updating strategy considering inertia-free velocity), and the direction search (DS) of Rosenbrock method, into the original PSO. With this hybrid, on the one hand, extensive exploration is still maintained by PSO; on the other hand, the SE is responsible for locating a small region, and then the DS further intensifies the search. The SDPSO algorithm was implemented and tested on unconstrained benchmark problems (CEC2014) and some constrained engineering design problems. The performance of SDPSO is compared with that of other optimization algorithms, and the results show that SDPSO has a competitive performance.

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