Evolving a Nelder–Mead Algorithm for Optimization with Genetic Programming

2017 ◽  
Vol 25 (3) ◽  
pp. 351-373 ◽  
Author(s):  
Iztok Fajfar ◽  
Janez Puhan ◽  
Árpád Bűrmen
Keyword(s):  
Genetic Programming ◽  
Optimization Algorithm ◽  
Optimization Method ◽  
Original Method ◽  
Quadratic Functions ◽  
Search Optimization ◽  
Standard Set ◽  
Downhill Simplex ◽  
Nelder Mead Algorithm ◽  
Better Than

We used genetic programming to evolve a direct search optimization algorithm, similar to that of the standard downhill simplex optimization method proposed by Nelder and Mead ( 1965 ). In the training process, we used several ten-dimensional quadratic functions with randomly displaced parameters and different randomly generated starting simplices. The genetically obtained optimization algorithm showed overall better performance than the original Nelder–Mead method on a standard set of test functions. We observed that many parts of the genetically produced algorithm were seldom or never executed, which allowed us to greatly simplify the algorithm by removing the redundant parts. The resulting algorithm turns out to be considerably simpler than the original Nelder–Mead method while still performing better than the original method.

scholarly journals Parameter Optimization for Ship Antiroll Gyros

2020 ◽  
Vol 10 (2) ◽  
pp. 661
Author(s):  
Yuanyuan Zhu ◽  
Shijie Su ◽  
Yuchen Qian ◽  
Yun Chen ◽  
Wenxian Tang
Keyword(s):  
Parameter Optimization ◽  
Optimization Algorithm ◽  
Optimal Parameter ◽  
Reduction Rate ◽  
Pattern Search ◽  
Random Waves ◽  
Search Optimization ◽  
Bacteria Foraging Optimization Algorithm ◽  
Parameter Values ◽  
Better Than

Ship antiroll gyros are a type of equipment used to reduce ships’ roll angle, and their parameters are related to the parameters of a ship and wave, which affect gyro performance. As an alternative framework, we designed a calculation method for roll reduction rate and considered random waves to establish a gyro parameter optimization model, and we then solved it through the bacteria foraging optimization algorithm (BFOA) and pattern search optimization algorithm (PSOA) to obtain optimal parameter values. Results revealed that the two methods could effectively reduce the overall mass and floor space of the antiroll gyro and improved its antirolling effect. In addition, the convergence speed and antirolling effect of the BFOA were better than that of the PSOA.

Parameters Optimization in SVM Based-On Ant Colony Optimization Algorithm

2010 ◽  
Vol 121-122 ◽  
pp. 470-475 ◽  
Author(s):  
Xiang Ying Liu ◽  
Hui Yan Jiang ◽  
Feng Zhen Tang
Keyword(s):  
Ant Colony Optimization ◽  
Optimization Algorithm ◽  
Particle Swarm Optimization Algorithm ◽  
Optimization Method ◽  
Parameters Optimization ◽  
Ant Colony ◽  
Trial And Error ◽  
Ant Colony Optimization Algorithm ◽  
Real World Datasets ◽  
Better Than

In this paper ACO (Ant Colony Optimization) algorithm, which is a well-known intelligent optimization method, is applied to selecting parameters for SVM.ACO has the characteristics of positive feedback, parallel mechanism and distributed computation. This paper gives comparison of ACO-SVM, PSO-SVM whose parameters are determined by particle swarm optimization algorithm, and traditional SVM whose parameters are decided through trial and error. The experimental results on real-world datasets show that this proposed method avoids randomness and subjectivity in the traditional SVM. Additionally it is able to gain better parameters which could dedicate to a higher classification accuracy than the PSO-SVM. Results confirm that proposed optimization method is better than the two others.

scholarly journals A modified simplex based direct search optimization algorithm for adaptive transversal FIR filters

2021 ◽  
Vol 104 (2) ◽  
pp. 003685042110254
Author(s):  
Armaghan Mohsin ◽  
Yazan Alsmadi ◽  
Ali Arshad Uppal ◽  
Sardar Muhammad Gulfam
Keyword(s):  
Optimization Algorithm ◽  
Optimization Technique ◽  
Fast Convergence ◽  
Good Convergence ◽  
Optimum Point ◽  
Search Optimization ◽  
Higher Dimensional ◽  
Gradient Based ◽  
Improved Accuracy ◽  
Quadratic Cost Function

In this paper, a novel modified optimization algorithm is presented, which combines Nelder-Mead (NM) method with a gradient-based approach. The well-known Nelder Mead optimization technique is widely used but it suffers from convergence issues in higher dimensional complex problems. Unlike the NM, in this proposed technique we have focused on two issues of the NM approach, one is shape of the simplex which is reshaped at each iteration according to the objective function, so we used a fixed shape of the simplex and we regenerate the simplex at each iteration and the second issue is related to reflection and expansion steps of the NM technique in each iteration, NM used fixed value of [Formula: see text], that is, [Formula: see text]  = 1 for reflection and [Formula: see text]  = 2 for expansion and replace the worst point of the simplex with that new point in each iteration. In this way NM search the optimum point. In proposed algorithm the optimum value of the parameter [Formula: see text] is computed and then centroid of new simplex is originated at this optimum point and regenerate the simplex with this centroid in each iteration that optimum value of [Formula: see text] will ensure the fast convergence of the proposed technique. The proposed algorithm has been applied to the real time implementation of the transversal adaptive filter. The application used to demonstrate the performance of the proposed technique is a well-known convex optimization problem having quadratic cost function, and results show that the proposed technique shows fast convergence than the Nelder-Mead method for lower dimension problems and the proposed technique has also good convergence for higher dimensions, that is, for higher filter taps problem. The proposed technique has also been compared with stochastic techniques like LMS and NLMS (benchmark) techniques. The proposed technique shows good results against LMS. The comparison shows that the modified algorithm guarantees quite acceptable convergence with improved accuracy for higher dimensional identification problems.

scholarly journals Application of energy dissipation and damping structure in the reinforcement of shear wall in concrete engineering

Open Physics ◽  
2020 ◽  
Vol 18 (1) ◽  
pp. 631-641
Author(s):  
Shujuan Yang
Keyword(s):  
Energy Dissipation ◽  
Design Process ◽  
Large Earthquake ◽  
Shear Wall ◽  
Original Method ◽  
Steel Technology ◽  
Dissipation Structure ◽  
Shear Damping ◽  
Better Than

AbstractIn view of the problem of large earthquake displacement in the use of the original concrete engineering shear wall reinforcement method, the energy dissipation and damping structure is used to design the energy dissipation and damping structure reinforcement method in the concrete engineering shear wall. According to the design process of the set method, the anti-vibration coefficient of the concrete shear wall is tested. The energy dissipation structure is used to construct a shear damping wall, and the damper is added to the original shear wall. The concrete shear wall is strengthened by sticking steel technology. So far, the design of shear wall reinforcement method based on the energy dissipation structure has been completed. Compared with the original method, the displacement distance of this method is lower than that of the original method. In conclusion, the effect of shear wall reinforcement method based on the energy dissipation structure is better than that of the original method.

A Mathematical Principle and Application on Design of Planar Six-Bar Mechanism with unto Three-Ordered Intermission at Limit Position(s)

2010 ◽  
Vol 37-38 ◽  
pp. 9-13
Author(s):  
Hong Xin Wang ◽  
Ning Dai
Keyword(s):  
Design Method ◽  
Optimization Method ◽  
Basic Function ◽  
Mathematical Principle ◽  
Transmission Characteristics ◽  
Basic Functions ◽  
Combined Mechanism ◽  
Limit Position ◽  
Derivatives Of ◽  
Better Than

A non-iterative design method about high order intermittent mechanisms is presented. The mathematical principle is that a compound function produced by two basic functions, and then one to three order derivatives of the compound function are all zeroes when one order derivative of each basic function is zero at the same moment. The design method is that a combined mechanism is constructed by six bars; the displacement functions of the front four-bar and back four-bar mechanisms are separately built, let one order derivatives of two displacement functions separately be zero at the same moment, and then get geometrical relationships and solution on the intermittent mechanism. A design example shows that this method is simpler and transmission characteristics are better than optimization method.

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