By Jason Brownlee

ISBN-10: 1446785068

ISBN-13: 9781446785065

This publication presents a guide of algorithmic recipes from the fields of Metaheuristics, Biologically encouraged Computation and Computational Intelligence which have been defined in a whole, constant, and centralized demeanour. those standardized descriptions have been conscientiously designed to be available, usable, and comprehensible. many of the algorithms defined during this publication have been initially encouraged by way of organic and normal platforms, resembling the adaptive services of genetic evolution and the obtained immune process, and the foraging behaviors of birds, bees, ants and micro organism. An encyclopedic set of rules reference, this booklet is meant for study scientists, engineers, scholars, and amateurs. every one set of rules description offers a operating code instance within the Ruby Programming Language.

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Jansen, and I. Wegener. Upper and lower bounds for randomized search heuristics in black-box optimization. Theory of Computing Systems, 39(4):525–544, 2006. 7. Bibliography 23 [20] A. P. Engelbrecht. Computational Intelligence: An Introduction. John Wiley and Sons, second edition, 2007. [21] D. Flanagan and Y. Matsumoto. The Ruby Programming Language. O’Reilly Media, 2008. [22] N. Forbes. Biologically inspired computing. Computing in Science and Engineering, 2(6):83–87, 2000. [23] N. Forbes. Imitation of Life: How Biology Is Inspiring Computing.

P. Engelbrecht. Computational Intelligence: An Introduction. John Wiley and Sons, second edition, 2007. [21] D. Flanagan and Y. Matsumoto. The Ruby Programming Language. O’Reilly Media, 2008. [22] N. Forbes. Biologically inspired computing. Computing in Science and Engineering, 2(6):83–87, 2000. [23] N. Forbes. Imitation of Life: How Biology Is Inspiring Computing. The MIT Press, 2005. [24] K. Fukunaga. Introduction to Statistical Pattern Recognition. Academic Press, 1990. [25] F. Glover and G.

10] E. Bonabeau, M. Dorigo, and G. Theraulaz. Swarm Intelligence: From Natural to Artificial Systems. Oxford University Press US, 1999. [11] S. Boyd and L. Vandenberghe. Convex Optimization. Cambridge University Press, 2004. [12] E. K. Burke, E. Hart, G. Kendall, J. Newall, P. Ross, and S. Schulenburg. Handbook of Metaheuristics, chapter Hyper-heuristics: An emerging direction in modern search technology, pages 457–474. Kluwer, 2003. [13] E. K. Burke, G. Kendall, and E. Soubeiga. A tabu-search hyperheuristic for timetabling and rostering.

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Clever Algorithms: Nature-Inspired Programming Recipes by Jason Brownlee


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