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001387343 020__ $$a9780262256032$$q(electronic bk.)
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001387343 020__ $$a141756041X$$q(electronic bk.)
001387343 020__ $$a9781417560417$$q(electronic bk.)
001387343 020__ $$a9780262042192$$q(alk. paper)
001387343 020__ $$a0262042193$$q(alk. paper)
001387343 035__ $$a(OCoLC)57182707$$z(OCoLC)290578252$$z(OCoLC)475377700$$z(OCoLC)646747529$$z(OCoLC)654766976$$z(OCoLC)722664915$$z(OCoLC)961534685$$z(OCoLC)962602017$$z(OCoLC)966106454$$z(OCoLC)988420881$$z(OCoLC)991905205$$z(OCoLC)991988074$$z(OCoLC)1037944525$$z(OCoLC)1038682983$$z(OCoLC)1055336112$$z(OCoLC)1081247619
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001387343 072_7 $$aMAT$$x042000$$2bisacsh
001387343 08204 $$a519.6$$222
001387343 1001_ $$aDorigo, Marco.
001387343 24510 $$aAnt colony optimization /$$cMarco Dorigo, Thomas Stützle.
001387343 260__ $$aCambridge, Mass. :$$bMIT Press,$$c©2004.
001387343 300__ $$a1 online resource (xi, 305 pages) :$$billustrations
001387343 336__ $$atext$$btxt$$2rdacontent
001387343 337__ $$acomputer$$bc$$2rdamedia
001387343 338__ $$aonline resource$$bcr$$2rdacarrier
001387343 500__ $$a"A Bradford book."
001387343 506__ $$aAccess limited to authorized users.
001387343 520__ $$aAn overview of the rapidly growing field of ant colony optimization that describes theoretical findings, the major algorithms, and current applications.The complex social behaviors of ants have been much studied by science, and computer scientists are now finding that these behavior patterns can provide models for solving difficult combinatorial optimization problems. The attempt to develop algorithms inspired by one aspect of ant behavior, the ability to find what computer scientists would call shortest paths, has become the field of ant colony optimization (ACO), the most successful and widely recognized algorithmic technique based on ant behavior. This book presents an overview of this rapidly growing field, from its theoretical inception to practical applications, including descriptions of many available ACO algorithms and their uses.The book first describes the translation of observed ant behavior into working optimization algorithms. The ant colony metaheuristic is then introduced and viewed in the general context of combinatorial optimization. This is followed by a detailed description and guide to all major ACO algorithms and a report on current theoretical findings. The book surveys ACO applications now in use, including routing, assignment, scheduling, subset, machine learning, and bioinformatics problems. AntNet, an ACO algorithm designed for the network routing problem, is described in detail. The authors conclude by summarizing the progress in the field and outlining future research directions. Each chapter ends with bibliographic material, bullet points setting out important ideas covered in the chapter, and exercises. Ant Colony Optimization will be of interest to academic and industry researchers, graduate students, and practitioners who wish to learn how to implement ACO algorithms.
001387343 588__ $$aOCLC-licensed vendor bibliographic record.
001387343 650_0 $$aMathematical optimization.
001387343 650_0 $$aAnts$$xBehavior$$xMathematical models.
001387343 653__ $$aCOMPUTER SCIENCE/General
001387343 655_0 $$aElectronic books
001387343 7001_ $$aStützle, Thomas.
001387343 852__ $$bebk
001387343 85640 $$3MIT Press$$uhttps://univsouthin.idm.oclc.org/login?url=https://doi.org/10.7551/mitpress/1290.001.0001?locatt=mode:legacy$$zOnline Access through The MIT Press Direct
001387343 85642 $$3OCLC metadata license agreement$$uhttp://www.oclc.org/content/dam/oclc/forms/terms/vbrl-201703.pdf
001387343 909CO $$ooai:library.usi.edu:1387343$$pGLOBAL_SET
001387343 980__ $$aBIB
001387343 980__ $$aEBOOK
001387343 982__ $$aEbook
001387343 983__ $$aOnline