Applications of Evolutionary Computation

1. Front Matter

   Pages I-XXV

   PDF

2. EvoBAFIN

   1. Front Matter

      Pages 1-1

      PDF

   2. Enhanced Multiobjective Population-Based Incremental Learning with Applications in Risk Treaty Optimization

      • Omar Andres Carmona Cortes, Andrew Rau-Chaplin

      Pages 3-18

   3. Genetic Programming with Memory For Financial Trading

      • Alexandros Agapitos, Anthony Brabazon, Michael O’Neill

      Pages 19-34

   4. Improving Fitness Functions in Genetic Programming for Classification on Unbalanced Credit Card Data

      • Van Loi Cao, Nhien-An Le-Khac, Michael O’Neill, Miguel Nicolau, James McDermott

      Pages 35-45

   5. Evolving Classification Models for Prediction of Patient Recruitment in Multicentre Clinical Trials Using Grammatical Evolution

      • Gilyana Borlikova, Michael Phillips, Louis Smith, Michael O’Neill

      Pages 46-57

   6. Portfolio Optimization, a Decision-Support Methodology for Small Budgets

      • Igor Deplano, Giovanni Squillero, Alberto Tonda

      Pages 58-72

   7. Evolutionary Multiobjective Optimization for Portfolios in Emerging Markets: Contrasting Higher Moments and Median Models

      • Mai A. Ibrahim, Mohammed El-Beltagy, Motaz Khorshid

      Pages 73-87

3. EvoBIO

   1. Front Matter

      Pages 89-89

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   2. On Combinatorial Optimisation in Analysis of Protein-Protein Interaction and Protein Folding Networks

      • David Chalupa

      Pages 91-105

   3. A Multi-objective Genetic Programming Biomarker Detection Approach in Mass Spectrometry Data

      • Soha Ahmed, Mengjie Zhang, Lifeng Peng, Bing Xue

      Pages 106-122

   4. Automating Biomedical Data Science Through Tree-Based Pipeline Optimization

      • Randal S. Olson, Ryan J. Urbanowicz, Peter C. Andrews, Nicole A. Lavender, La Creis Kidd, Jason H. Moore

      Pages 123-137

   5. Bicliques in Graphs with Correlated Edges: From Artificial to Biological Networks

      • Aaron Kershenbaum, Alicia Cutillo, Christian Darabos, Keitha Murray, Robert Schiaffino, Jason H. Moore

      Pages 138-155

   6. Hybrid Biclustering Algorithms for Data Mining

      • Patryk Orzechowski, Krzysztof Boryczko

      Pages 156-168

   7. Discovering Potential Clinical Profiles of Multiple Sclerosis from Clinical and Pathological Free Text Data with Constrained Non-negative Matrix Factorization

      • Jacopo Acquarelli, The Netherlands Brain Bank, Monica Bianchini, Elena Marchiori

      Pages 169-183

   8. Application of Evolutionary Algorithms for the Optimization of Genetic Regulatory Networks

      • Elise Rosati, Morgan Madec, Abir Rezgui, Quentin Colman, Nicolas Toussaint, Christophe Lallement et al.

      Pages 184-200

4. EvoCOMNET

   1. Front Matter

      Pages 201-201

      PDF

   2. A Hybrid Discrete Artificial Bee Colony Algorithm for the Multicast Routing Problem

      • Yannis Marinakis, Magdalene Marinaki, Athanasios Migdalas

      Pages 203-218

   3. Evolving Coverage Optimisation Functions for Heterogeneous Networks Using Grammatical Genetic Programming

      • Michael Fenton, David Lynch, Stepan Kucera, Holger Claussen, Michael O’Neill

      Pages 219-234

   4. Joint Topology Optimization, Power Control and Spectrum Allocation for Intra-Vehicular Multi-hop Sensor Networks Using Dandelion-Encoded Heuristics

      • Javier Del Ser, Miren Nekane Bilbao, Cristina Perfecto, Antonio Gonzalez-Pardo, Sergio Campos-Cordobes

      Pages 235-250

The two volumes LNCS 9597 and 9598 constitute the refereed conference proceedings of the 19th European Conference on the Applications of Evolutionary Computation, EvoApplications 2016, held in Porto, Portugal, in March/April 2016, co-located with the Evo* 2016 events EuroGP, EvoCOP, and EvoMUSART.

The 57 revised full papers presented together with 17 poster papers were carefully reviewed and selected from 115 submissions. EvoApplications 2016 consisted of the following 13 tracks: EvoBAFIN (natural computing methods in business analytics and finance), EvoBIO (evolutionary computation, machine learning and data mining in computational biology), EvoCOMNET (nature-inspired techniques for telecommunication networks and other parallel and distributed systems), EvoCOMPLEX (evolutionary algorithms and complex systems), EvoENERGY (evolutionary computation in energy applications), EvoGAMES (bio-inspired algorithms in games), EvoIASP (evolutionary computation in image analysis, signal processing, and pattern recognition), EvoINDUSTRY (nature-inspired techniques in industrial settings), EvoNUM (bio-inspired algorithms for continuous parameter optimization), EvoPAR (parallel implementation of evolutionary algorithms), EvoRISK (computational intelligence for risk management, security and defence applications), EvoROBOT (evolutionary robotics), and EvoSTOC (evolutionary algorithms in stochastic and dynamic environments).

• Artificial intelligence
• Bioinspired methods
• Biologically inspired computing
• Combinatorial optimization
• Communication networks
• Complex systems
• Computer games
• Data mining
• Distributed systems
• Energy applications
• Evolutionary algorithms
• Evolutionary computation
• Feature selection
• Finance and economics
• Genetic algorithms
• Genetic programming
• Machine learning
• Natural computing
• Particle Swarm Optimization (PSO)
• Problem solving

• Politecnico di Torino, Turin, Italy

  Giovanni Squillero

• Aalborg University, Copenhagen, Denmark

  Paolo Burelli

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