A Selected Introduction to Evolutionary Computation

There have been many different views and definitions about evolu- tionary computation. Some regard evolutionary computation as genetic algorithms (GAs), although GAs are only one of many possible types of evolutionary algorithms (EAs). In this chapter, we will take a much broader view of what evolutionary computation is by emphasizing its computational nature. In short, evolutionary computation refers to the study of computational systems that use ideas and draw inspirations from natural evolution. Evolutionary computation techniques can be used to solve a wide range of practical problems in optimization, machine learning and design. This chapter gives a brief introduction to evolutionary computation. A few important issues that may have been overlooked in evolutionary computation will be emphasized. Pointers to further details in the literature will be given whenever appropriate.

[1]  Xin Yao,et al.  Evolutionary ensembles with negative correlation learning , 2000, IEEE Trans. Evol. Comput..

[2]  C. H. Edwards,et al.  Calculus with analytic geometry , 1994 .

[3]  David B. Fogel,et al.  An introduction to simulated evolutionary optimization , 1994, IEEE Trans. Neural Networks.

[4]  Xin Yao,et al.  Evolutionary programming made faster , 1999, IEEE Trans. Evol. Comput..

[5]  Xin Yao,et al.  Simulated annealing with extended neighbourhood , 1991, Int. J. Comput. Math..

[6]  Xin Yao,et al.  Materialized view selection as constrained evolutionary optimization , 2003, IEEE Trans. Syst. Man Cybern. Part C.

[7]  Thomas Bäck,et al.  An Overview of Evolutionary Algorithms for Parameter Optimization , 1993, Evolutionary Computation.

[8]  Xin Yao,et al.  Making use of population information in evolutionary artificial neural networks , 1998, IEEE Trans. Syst. Man Cybern. Part B.

[9]  Xin Yao,et al.  Speciation as automatic categorical modularization , 1997, IEEE Trans. Evol. Comput..

[10]  X. Yao,et al.  Analysing crossover operators by search step size , 1997, Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97).

[11]  Xin Yao,et al.  Evolutionary programming using mutations based on the Levy probability distribution , 2004, IEEE Transactions on Evolutionary Computation.

[12]  Xin Yao,et al.  Stochastic ranking for constrained evolutionary optimization , 2000, IEEE Trans. Evol. Comput..

[13]  Xin Yao,et al.  From an individual to a population: an analysis of the first hitting time of population-based evolutionary algorithms , 2002, IEEE Trans. Evol. Comput..