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Applications of Evolutionary Computation : EvoApplications 2012: EvoCOMNET, EvoCOMPLEX, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoNUM, EvoPAR, EvoRISK, EvoSTIM, and EvoSTOC, Malaga, Spain, April 11-13, 20, PDF eBook

Applications of Evolutionary Computation : EvoApplications 2012: EvoCOMNET, EvoCOMPLEX, EvoFIN, EvoGAMES, EvoHOT, EvoIASP, EvoNUM, EvoPAR, EvoRISK, EvoSTIM, and EvoSTOC, Malaga, Spain, April 11-13, 20 PDF

Edited by Cecilia Di Chio, Alexandros Agapitos, Stefano Cagnoni, Carlos Cotta, Francisco Fernandez de Vega, Gianni A. Di Caro, Rolf Drechsler, Aniko Ekart, Anna I. Esparcia-Alcazar, Muddassar Farooq, W.B. Langdon, Juan-J. Merelo-Guervos, Mike Preuss, Hendrik Richter, Sara Silva, Anabela Simoes, Giovanni Squillero, Ernesto Tarantino, Andrea Tettamanzi, Julian Togelius, Neil Urquhart, Sima Uyar, Georgios N. Yannakakis

Part of the Lecture Notes in Computer Science series

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Description

This book constitutes the refereed proceedings of the International Conference on the Applications of Evolutionary Computation, EvoApplications 2012, held in Malaga, Spain, in April 2012, colocated with the Evo* 2012 events EuroGP, EvoCOP, EvoBIO, and EvoMUSART.

The 54 revised full papers presented were carefully reviewed and selected from 90 submissions.

EvoApplications 2012 consisted of the following 11 tracks: EvoCOMNET (nature-inspired techniques for telecommunication networks and other parrallel and distributed systems), EvoCOMPLEX (algorithms and complex systems), EvoFIN (evolutionary and natural computation in finance and economics), EvoGAMES (bio-inspired algorithms in games), EvoHOT (bio-inspired heuristics for design automation), EvoIASP (evolutionary computation in image analysis and signal processing), EvoNUM (bio-inspired algorithms for continuous parameter optimization), EvoPAR (parallel implementation of evolutionary algorithms), EvoRISK (computational intelligence for risk management, security and defense applications), EvoSTIM (nature-inspired techniques in scheduling, planning, and timetabling), and EvoSTOC (evolutionary algorithms in stochastic and dynamic environments).

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