Giovanni Squillero – författare
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This book describes an award-winning evolutionary algorithm that outperformed experts and conventional heuristics in solving several industrial problems. It presents a discussion of the theoretical and practical aspects that enabled μGP (MicroGP) to autonomously find the optimal solution of hard problems, handling highly structured data, such as full-fledged assembly programs, with functions and interrupt handlers.
For a practitioner, μGP is simply a versatile optimizer to tackle most problems with limited setup effort. The book is valuable for all who require heuristic problem-solving methodologies, such as engineers dealing with verification and test of electronic circuits; or researchers working in robotics and mobile communication. Examples are provided to guide the reader through the process, from problem definition to gathering results.
For an evolutionary computation researcher, μGP may be regarded as a platform where new operators and strategies can be easily tested.
MicroGP (the toolkit) is an active project hosted by Sourceforge: http://ugp3.sourceforge.net/
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Applications of Evolutionary Computation
18th European Conference, EvoApplications 2015, Copenhagen, Denmark, April 8-10, 2015, Proceedings
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Applications of Evolutionary Computation
19th European Conference, EvoApplications 2016, Porto, Portugal, March 30 -- April 1, 2016, Proceedings, Part II
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Thetwo volumes LNCS 9597 and 9598 constitute the refereed conference proceedingsof the 19th European Conference on the Applications of Evolutionary Computation,EvoApplications 2016, held in Porto, Portugal, in March/April 2016, co-locatedwith the Evo* 2016 events EuroGP, EvoCOP, and EvoMUSART.
The57 revised full papers presented together with 17 poster papers were carefullyreviewed and selected from 115 submissions. EvoApplications 2016 consisted ofthe following 13 tracks: EvoBAFIN (natural computing methods in businessanalytics and finance), EvoBIO (evolutionary computation, machine learning anddata mining in computational biology), EvoCOMNET (nature-inspired techniquesfor telecommunication networks and other parallel and distributed systems),EvoCOMPLEX (evolutionary algorithms and complex systems), EvoENERGY(evolutionary computation in energy applications), EvoGAMES (bio-inspiredalgorithms in games), EvoIASP (evolutionary computation in image analysis,signal processing, and pattern recognition), EvoINDUSTRY (nature-inspiredtechniques in industrial settings), EvoNUM (bio-inspired algorithms forcontinuous parameter optimization), EvoPAR (parallel implementation ofevolutionary algorithms), EvoRISK (computational intelligence for riskmanagement, security and defence applications), EvoROBOT (evolutionaryrobotics), and EvoSTOC (evolutionary algorithms in stochastic and dynamicenvironments).Applications of Evolutionary Computation
19th European Conference, EvoApplications 2016, Porto, Portugal, March 30 -- April 1, 2016, Proceedings, Part I
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Thetwo volumes LNCS 9597 and 9598 constitute the refereed conference proceedingsof the 19th European Conference on the Applications of Evolutionary Computation,EvoApplications 2016, held in Porto, Portugal, in March/April 2016, co-locatedwith the Evo* 2016 events EuroGP, EvoCOP, and EvoMUSART.
The 57 revised full papers presented together with17 poster papers were carefully reviewed and selected from 115 submissions.EvoApplications 2016 consisted of the following 13 tracks: EvoBAFIN (naturalcomputing methods in business analytics and finance), EvoBIO (evolutionarycomputation, machine learning and data mining in computational biology), EvoCOMNET(nature-inspired techniques for telecommunication networks and other paralleland distributed systems), EvoCOMPLEX (evolutionary algorithms and complex systems),EvoENERGY (evolutionary computation in energy applications), EvoGAMES(bio-inspired algorithms in games), EvoIASP (evolutionary computation in imageanalysis, signal processing, and pattern recognition), EvoINDUSTRY(nature-inspired techniques in industrial settings), EvoNUM (bio-inspiredalgorithms for continuous parameter optimization), EvoPAR (parallelimplementation of evolutionary algorithms), EvoRISK (computational intelligencefor risk management, security and defence applications), EvoROBOT (evolutionaryrobotics), and EvoSTOC (evolutionary algorithms in stochastic and dynamicenvironments).Applications of Evolutionary Computation
20th European Conference, EvoApplications 2017, Amsterdam, The Netherlands, April 19-21, 2017, Proceedings, Part II
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Applications of Evolutionary Computation
20th European Conference, EvoApplications 2017, Amsterdam, The Netherlands, April 19-21, 2017, Proceedings, Part I
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561 kr
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Industrial Applications of Evolutionary Algorithms
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"Industrial applications of evolutionary algorithms" is intended as a resource for both experienced users of evolutionary algorithms and researchers that are beginning to approach these fascinating optimization techniques.
Experienced users will find interesting details of real-world problems, advice on solving issues related to fitness computation or modeling, and suggestions on how to set the appropriate parameters to reach optimal solutions.
Beginners will find a thorough introduction to evolutionary computation, and a complete presentation of several classes of evolutionary algorithms exploited to solve different problems. Inside, scholars will find useful examples on how to fill the gap between purely theoretical examples and industrial problems.
The collection of case studies presented is also extremely appealing for anyone interested in Evolutionary Computation, but without direct access to extensive technical literature on the subject.
After the introduction, each chapter in the book presents a test case, and is organized so that it can be read independently from the rest: all the information needed to understand the problem and the approach is reported in each part. Chapters are grouped by three themes of particular interest for real-world applications, namely prototype-based validation, reliability and test generation.
The authors hope that this volume will help to expose the flexibility and efficiency of evolutionary techniques, encouraging more companies to adopt them; and that, most of all, you will enjoy your reading.
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Industrial Applications of Evolutionary Algorithms
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