An evolutionary programming algorithm for automatic engineering design

- 01 Dec 2004

- Vol. 3019, pp 586-594

TL;DR: This paper describes a new Evolutionary Programming algorithm based on Self-Organised Criticality that is capable of delivering high quality results faster, and is simple, robust and highly parallel.

Abstract: This paper describes a new Evolutionary Programming algorithm based on Self-Organised Criticality. When tested on a range of problems drawn from real-world applications in science and engineering, it performed better than a variety of gradient descent, direct search and genetic algorithms. It proved capable of delivering high quality results faster, and is simple, robust and highly parallel.

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This paper describes a new Evolutionary Programming algorithm based on Self-Organised Criticality.

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Further work is required on EPSOC to determine the efficacy of the method on problems of high dimensionality, and the link between problem dimensionality and optimal population size, extinction rates and mutation factors.

Table 1. Best objective functions values obtained in 10 runs, and time taken

Fig. 1. a taxonomy of optimisation algorithms

Citations

•Journal Article•10.1016/J.KNOSYS.2017.12.037

Evolutionary Population Dynamics and Grasshopper Optimization approaches for feature selection problems

Majdi Mafarja, +6 more

- 01 Dec 2017

- Knowledge Based Systems

TL;DR: The comprehensive results and various comparisons reveal that the EPD has a remarkable impact on the efficacy of the GOA and using the selection mechanism enhanced the capability of the proposed approach to outperform other optimizers and find the best solutions with improved convergence trends.

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•Journal Article•10.1016/J.ASOC.2015.04.061

Distributed evolutionary algorithms and their models

Yue-Jiao Gong, +6 more

- 01 Sep 2015

TL;DR: A comprehensive survey of the state-of-the-art distributed evolutionary algorithms and models, which have been classified into two groups according to their task division mechanism, and insights into the models are presented and discussed.

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Journal Article•10.1007/S00521-014-1806-7

Evolutionary population dynamics and grey wolf optimizer

Shahrzad Saremi, +2 more

- 01 Jul 2015

- Neural Computing and Applications

TL;DR: The proposed GWO–EPD algorithm is benchmarked on six unimodal and seven multi-modal test functions and is demonstrated that the proposed operator is able to significantly improve the performance of the GWO algorithm in terms of exploration, local optima avoidance, exploitation, local search, and convergence rate.

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Journal Article•10.1016/J.INS.2016.01.068

An adaptive multi-population differential evolution algorithm for continuous multi-objective optimization

Xianpeng Wang, +1 more

- 20 Jun 2016

- Information Sciences

TL;DR: An adaptive differential evolution algorithm based on analysis of search data is developed for the multi-objective optimization problems and it is shown that the improvements of the strategies are positive and that it is competitive or superior to some previous multi- objective evolutionary algorithms in the literature.

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Journal Article•10.1016/J.SOLENER.2012.04.009

An intelligent method for sizing optimization in grid-connected photovoltaic system

Shahril Irwan Sulaiman, +4 more

- 01 Jul 2012

- Solar Energy

TL;DR: Results showed that the EPSA had outperformed ISA in terms of producing lower computation time and had also shown the best optimization performance when compared with other intelligent-based sizing algorithms using different types of Computational Intelligence.

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References

Journal Article•10.1093/COMJNL/7.4.308

A simplex method for function minimization

John A. Nelder, +1 more

- 01 Jan 1965

- The Computer Journal

TL;DR: A method is described for the minimization of a function of n variables, which depends on the comparison of function values at the (n 41) vertices of a general simplex, followed by the replacement of the vertex with the highest value by another point.

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30.6K

Direct search methods: Once scorned, now respectable

Margaret H. Wright

- 01 Jan 1996

352

•Proceedings Article•10.1145/582034.582059

An Automatic Design Optimization Tool and its Application to Computational Fluid Dynamics

David Abramson, +3 more

- 10 Nov 2001

TL;DR: The paper describes the Nimrod/O system, and then discusses a case study in the evaluation of an aerofoil problem, showing that the general approach is extremely flexible and delivers better results than a program that was developed specifically for the problem.

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•Proceedings Article

A combined nelder-mead simplex and genetic algorithm

Nicolas Durand, +1 more

- 13 Jul 1999

TL;DR: In this article, a combined Nelder-Mead Simplex and Genetic algorithm is introduced and tested on classical test functions on which both genetic algorithm or local optimization techniques are not efficient when separately used.

...read moreread less

•Book Chapter•10.1007/978-3-540-24669-5_96

Optimization Using Nimrod/O and Its Application to Robust Mechanical Design

Thomas Charles Peachey, +4 more

- 07 Sep 2003

TL;DR: The experiment reveals two distinct design strategies for optimizing this life in the presence of flaws and Nimrod/O is able to find both of these rapidly due to its inherent parallelism.

...read moreread less

An evolutionary programming algorithm for automatic engineering design

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Citations

Evolutionary Population Dynamics and Grasshopper Optimization approaches for feature selection problems

Distributed evolutionary algorithms and their models

Evolutionary population dynamics and grey wolf optimizer

An adaptive multi-population differential evolution algorithm for continuous multi-objective optimization

An intelligent method for sizing optimization in grid-connected photovoltaic system

References

A simplex method for function minimization

Direct search methods: Once scorned, now respectable

An Automatic Design Optimization Tool and its Application to Computational Fluid Dynamics

A combined nelder-mead simplex and genetic algorithm

Optimization Using Nimrod/O and Its Application to Robust Mechanical Design

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