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Some interesting features of the new book "Introduction to Evolutionary Algorithms", which is written by Xinjie Yu and Mitsuo Gen and be published by Springer in 2010, will be illustrated, including covering nearly all the hot evolutionary-computation-related topics, referring to the latest published journal papers, introducing the applications of EAs as many as possible, and adopting many pedagogical ways to make EAs easy and interesting.The contents and the consideration of selecting these contents will be discussed. Then the focus will be put on the pedagogical ways for teaching and self-study.The algorithms introduced in the tutorial include constrained optimization evolutionary algorithms (COEA), multiobjective evolutionary algorithms (MOEA), ant colony optimization (ACO), particle swarm optimization (PSO), and artificial immune systems (AIS). Some of the applications of these evolutionary algorithms will be discussed.

A novel algorithm for digital infinite-impulse response (IIR) filter design is proposed in this paper. The suggested algorithm is a kind of cooperative coevolutionary genetic algorithm. It considers the magnitude response and the phase response simultaneously and also tries to find the lowest filter order. The structure and the coefficients of the digital IIR filter are coded separately, and they evolve coordinately as two different species, i.e., the control species and the coefficient species. The nondominated sorting genetic algorithm-II is used for the control species to guide the algorithms toward three objectives simultaneously. The simulated annealing is used for the coefficient species to keep the diversity. These two strategies make the cooperative coevolutionary process work effectively. Comparisons with another genetic algorithm-based digital IIR filter design method by numerical experiments show that the suggested algorithm is effective and robust in digital IIR filter design.

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