论文信息 - An Evolutionary Programming Algorithm for Automatic Engineering Design

An Evolutionary Programming Algorithm for Automatic Engineering Design

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.

[1] John A. Nelder,et al. A Simplex Method for Function Minimization , 1965, Comput. J..

[2] Jarmo T. Alander,et al. An Indexed Bibliography of Genetic Algorithms in Computer Aided Design , 1995 .

[3] R. Fletcher. Practical Methods of Optimization , 1988 .

[4] D. Abramson,et al. An Automatic Design Optimization Tool and its Application to Computational Fluid Dynamics , 2001, ACM/IEEE SC 2001 Conference (SC'01).

[5] Andrew Lewis,et al. Optimization Using Nimrod/O and Its Application to Robust Mechanical Design , 2003, PPAM.

[6] J. Alliot,et al. A combined nelder-mead simplex and genetic algorithm , 1999 .

[7] K. Mellanby. How Nature works , 1978, Nature.

[8] T. Krink,et al. Self-organized criticality and mass extinction in evolutionary algorithms , 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

[9] Margaret H. Wright,et al. Direct search methods: Once scorned, now respectable , 1996 .

[10] David Abramson,et al. Nimrod: a tool for performing parametrised simulations using distributed workstations , 1995, Proceedings of the Fourth IEEE International Symposium on High Performance Distributed Computing.

[11] Andrew Lewis,et al. An application of optimisation for passive RF Component design , 2000 .

[12] D. Abramson,et al. Parallel Non-Linear Optimization : Towards The Design Of A Decision Support System For Air Quality Management , 1997, ACM/IEEE SC 1997 Conference (SC'97).