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ORCIDGenetic Programming and Evolvable Machines, Volume 19
Volume 19, Numbers 1-2, June 2018
- Lee Spector:
Editorial introduction. 1-2 - Lee Spector:
Acknowledgment to reviewers. 3-4 - Su Nguyen
, Yi Mei, Mengjie Zhang:
Guest editorial: special issue on automated design and adaptation of heuristics for scheduling and combinatorial optimisation. 5-7 - Marko Durasevic, Domagoj Jakobovic:
Evolving dispatching rules for optimising many-objective criteria in the unrelated machines environment. 9-51 - Marko Durasevic, Domagoj Jakobovic:
Comparison of ensemble learning methods for creating ensembles of dispatching rules for the unrelated machines environment. 53-92 - Rinde R. S. van Lon, Jürgen Branke, Tom Holvoet:
Optimizing agents with genetic programming: an evaluation of hyper-heuristics in dynamic real-time logistics. 93-120 - Mohamed El Yafrani, Marcella S. R. Martins, Markus Wagner, Belaïd Ahiod, Myriam Regattieri Delgado, Ricardo Lüders:
A hyperheuristic approach based on low-level heuristics for the travelling thief problem. 121-150 - Juan-Carlos Gomez, Hugo Terashima-Marín:
Evolutionary hyper-heuristics for tackling bi-objective 2D bin packing problems. 151-181 - Ayad Turky, Nasser R. Sabar, Andy Song:
Cooperative evolutionary heterogeneous simulated annealing algorithm for google machine reassignment problem. 183-210 - Oscar Garnica, Kyrre Glette, Jim Tørresen:
Comparing three online evolvable hardware implementations of a classification system. 211-234 - Jack Mario Mingo, Ricardo Aler:
Evolution of shared grammars for describing simulated spatial scenes with grammatical evolution. 235-270 - David Moskowitz:
Implementing the template method pattern in genetic programming for improved time series prediction. 271-299 - Christine Zarges:
Hod Lipson and Melba Kurman: Driverless: intelligent cars and the road ahead - The MIT Press, 2016, pp 312, ISBN: 9780262035224. 301-303 - Jeff Heaton:
Ian Goodfellow, Yoshua Bengio, and Aaron Courville: Deep learning - The MIT Press, 2016, 800 pp, ISBN: 0262035618. 305-307 - Ofer M. Shir:
Christian Blum and Günther R. Raidl: Hybrid metaheuristics - powerful tools for optimization - Springer International Publishing, Switzerland, 2016, 157 pp, ISBN: 978-3-319-30882-1. 309-311
Volume 19, Number 3, September 2018
- Nadia Boukhelifa, Evelyne Lutton:
Guest editorial: Special issue on genetic programming, evolutionary computation and visualization. 313-315 - Nadarajen Veerapen, Gabriela Ochoa:
Visualising the global structure of search landscapes: genetic improvement as a case study. 317-349 - Eric Medvet, Marco Virgolin, Mauro Castelli, Peter A. N. Bosman, Ivo Gonçalves, Tea Tusar:
Unveiling evolutionary algorithm representation with DU maps. 351-389 - Cameron C. Gray, Shatha F. Al-Maliki, Franck Patrick Vidal:
Data exploration in evolutionary reconstruction of PET images. 391-419 - David J. Walker:
Visualisation with treemaps and sunbursts in many-objective optimisation. 421-452 - Peter Karpov, Giovanni Squillero, Alberto Paolo Tonda:
VALIS: an evolutionary classification algorithm. 453-471
Volume 19, Number 4, December 2018
- Iztok Fajfar, Árpád Bürmen, Janez Puhan:
Grammatical evolution as a hyper-heuristic to evolve deterministic real-valued optimization algorithms. 473-504 - Azam Shirali, Javidan Kazemi Kordestani, Mohammad Reza Meybodi:
Self-adaptive multi-population genetic algorithms for dynamic resource allocation in shared hosting platforms. 505-534 - Tiantian Dou, Peter I. Rockett:
Comparison of semantic-based local search methods for multiobjective genetic programming. 535-563 - Keith L. Downing:
Alain Pétrowski and Sana Ben-Hamida: Evolutionary Algorithms - John Wiley and Sons, Inc., Hoboken, New Jersey, USA, 2017, ISBN-13: 978-1848218048, ISBN-10: 1848218044. 565-566 - Spyridon Samothrakis:
Kathryn E. Merrick: Computational models of motivation for game-playing agents - Springer, 2016, 213 pp, ISBN: 978-3-319-33457-8. 567-568 - Analía Amandi:
Ryan J. Urbanowicz, and Will N. Browne: Introduction to learning classifier systems - Springer, 2017, 123 pp, ISBN 978-3-662-55007-6. 569-570
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