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ORCIDGECCO 2019: Prague, Czech Republic - Companion Material
- Manuel López-Ibáñez, Anne Auger, Thomas Stützle:
Proceedings of the Genetic and Evolutionary Computation Conference Companion, GECCO 2019, Prague, Czech Republic, July 13-17, 2019. ACM 2019, ISBN 978-1-4503-6748-6
Competition entry: Competition internet of things - Online event detection for drinking water quality control
- Victor Henrique Alves Ribeiro
, Gilberto Reynoso-Meza:
Monitoring of drinking-water quality by means of a multi-objective ensemble learning approach. 1-2
Competition entry: Competition 100-digit challenge
- Quoc Bao Diep, Ivan Zelinka, Swagatam Das:
Self-organizing migrating algorithm for the 100-digit challenge. 3-4 - Takeshi Kawachi, Jun-ichi Kushida, Akira Hara, Tetsuyuki Takahama:
L-SHADE with an adaptive penalty method of balancing the objective value and the constraint violation. 5-6 - Fernando Lezama, João P. Soares, Ricardo Faia, Zita A. Vale:
Hybrid-adaptive differential evolution with decay function (HyDE-DF) applied to the 100-digit challenge competition on single objective numerical optimization. 7-8 - Tao Xu, Jun He, Changjing Shang:
Helper and equivalent objective different evolution for constrained optimisation. 9-10 - Ales Zamuda:
Function evaluations upto 1e+12 and large population sizes assessed in distance-based success history differential evolution for 100-digit challenge and numerical optimization scenarios (DISHchain 1e+12): a competition entry for "100-digit challenge, and four other numerical optimization competitions" at the genetic and evolutionary computation conference (CECCO) 2019. 11-12
Competition entry: Competition evolutionary computation in uncertain environments - A smart grid application
- Yoan Martínez López, Ansel Y. Rodríguez González, Julio Madera Quintana, Alexis Moya, Bismay Morgado, Miguel Betancourt Mayedo:
CUMDANCauchy-C1: a cellular EDA designed to solve the energy resource management problem under uncertainty. 13-14
Competition entry: Competition AI competition for the legends of the three kingdoms game
- Youjie Zhang, Xiang Ding, Zhi Chen:
Solving legends of the three kingdoms based on hierarchical macro strategy model. 15-16
Hot off the press
- Lukás Bajer, Zbynek Pitra, Jakub Repický, Martin Holena:
Gaussian process surrogate models for the CMA-ES. 17-18 - Roman Denysiuk, António Gaspar-Cunha, Alexandre C. B. Delbem:
Combining artificial neural networks and evolution to solve multiobjective knapsack problems. 19-20 - Tome Eftimov, Peter Korosec:
Understanding exploration and exploitation powers of meta-heuristic stochastic optimization algorithms through statistical analysis. 21-22 - Daniel Hein, Steffen Udluft, Thomas A. Runkler:
Generating interpretable reinforcement learning policies using genetic programming. 23-24 - Johannes Lengler, Anders Martinsson, Angelika Steger:
The (1 + 1)-EA with mutation rate (1 + ϵ)/n is efficient on monotone functions: an entropy compression argument. (hot-off-the-press track at GECCO 2019). 25-26 - Krzysztof Michalak:
Low-Dimensional euclidean embedding for visualization of search spaces in combinatorial optimization. 27-28 - Jason H. Moore, Randal S. Olson, Yong Chen, Moshe Sipper:
Discovering test statistics using genetic programming. 29-30 - Patryk Orzechowski, Jason H. Moore:
EBIC: a scalable biclustering method for large scale data analysis. 31-32 - Inês Soares, Maria João Alves, Carlos Henggeler Antunes:
A bi-level hybrid PSO: MIP solver approach to define dynamic tariffs and estimate bounds for an electricity retailer profit. 33-34 - Jerry Swan, Krzysztof Krawiec, Zoltan A. Kocsis:
Stochastic program synthesis via recursion schemes. 35-36 - William B. Yates, Edward C. Keedwell:
Analysing heuristic subsequences for offline hyper-heuristic learning. 37-38 - Ales Zamuda, José Daniel Hernández Sosa:
Hot off the press in expert systems on underwater robotic missions: success history applied to differential evolution for underwater glider path planning. 39-40
Late-breaking abstract
- Nader Azad, Adel Aazami, Ali Papi, Armin Jabbarzadeh:
A two-phase genetic algorithm for incorporating environmental considerations with production, inventory and routing decisions in supply chain networks. 41-42 - Mayowa Ayodele:
Application of estimation of distribution algorithm for feature selection. 43-44 - Mayowa Ayodele, K. Nadia Papamichail, Geraldine Gallagher, Darren Buckley:
Hybrid estimation of distribution algorithm for solving a resource level allocation problem in a legal business. 45-46 - Pietro Barbiero, Giovanni Squillero, Alberto Paolo Tonda:
Beyond coreset discovery: evolutionary archetypes. 47-48 - Amit Benbassat:
Genetic algorithms are very good solved sudoku generators. 49-50 - Hwi-Yeon Cho, Yong-Hyuk Kim:
Stabilized training of generative adversarial networks by a genetic algorithm. 51-52 - José Ignacio Hidalgo, Ricardo Fernández, Oscar Garnica, J. Manuel Colmenar, Juan Lanchares, Gaspar González-Doncel:
Determination of microscopic residual stresses using diffraction methods, EBSD maps, and evolutionary algorithms. 53-54 - Ingmar Kanitscheider, Bowen Baker, Todor M. Markov, Igor Mordatch:
Skill emergence and transfer in multi-agent environments. 55-56 - Ahmed Kheiri, Konstantinos Zografos:
Modelling and solving the combined inventory routing problem with risk consideration. 57-58 - Man-Je Kim, Jun Suk Kim, Donghyeon Lee, Sungjin James Kim, Min-Jung Kim, Chang Wook Ahn:
Integrating agent actions with genetic action sequence method. 59-60 - Yong-Hoon Kim, Junghwan Lee, Yong-Hyuk Kim:
Predictive model for epistasis-based basis evaluation on pseudo-boolean function using deep neural networks. 61-62 - William B. Langdon:
Parallel GPQUICK. 63-64 - Seung-Ju Lee, Hyun-Ji Moon, Da-Jung Kim, Yourim Yoon:
Genetic algorithm-based feature selection for depression scale prediction. 65-66 - Piotr Lipinski, Krzysztof Michalak:
Multidimensional time series feature engineering by hybrid evolutionary approach. 67-68 - Carolina Gil Marcelino, Carlos Eduardo Pedreira, Elizabeth F. Wanner, Leonel M. Carvalho, Vladimiro Miranda, Armando L. da Silva:
CE+EPSO: a merged approach to solve SCOPF problem. 69-70 - Alejandro Marrero, Eduardo Segredo, Coromoto León:
On the automatic planning of healthy and balanced menus. 71-72 - Yukiko Orito, Tomoko Kashima:
EDA with hamming distance for consumption-loan planning in experimental economics. 73-74 - Lia T. Parsenadze, Danilo Vasconcellos Vargas, Toshiyuki Fujita:
Towards solving neural networks with optimization trajectory search. 75-76 - Mariem Sebai, Ezzeddine Fatnassi, Lilia Rejeb:
A honeybee mating optimization algorithm for solving the static bike rebalancing problem. 77-78 - Aviv Segev, Rituparna Datta, Ryan Benton, Dorothy Curtis:
OINNIONN: outward inward neural network and inward outward neural network evolution. 79-80 - Alexander V. Spirov, Ekaterina M. Myasnikova:
Techniques from evolutionary computation to implement as experimental approaches in synthetic biology: tests in silico. 81-82 - Vladimir Stanovov, Shakhnaz Akhmedova, Eugene Semenkin:
Selective pressure in constrained differential evolution. 83-84 - Dana Vrajitoru:
Trajectory optimization for car races using genetic algorithms. 85-86 - Pak-Kan Wong, Man-Leung Wong, Kwong-Sak Leung:
Probabilistic grammar-based deep neuroevolution. 87-88 - Yapei Wu, Xingguang Peng, Demin Xu:
Identifying variable interaction using mutual information of multiple local optima. 89-90 - Dong-Pil Yu, Yong-Hyuk Kim:
Predictability on performance of surrogate-assisted evolutionary algorithm according to problem dimension. 91-92 - Guohai Zhu, Kewei Yang, Qingsong Zhao, Zhiwei Yang:
Bi-objective optimal planning for emergency resource allocation in the maritime oil spill accident response phase under uncertainty. 93-94 - Wiem Zouari, Inès Alaya, Moncef Tagina:
A new hybrid ant colony algorithms for the traveling thief problem. 95-96
Poster: Ant colony optimization and swarm intelligence
- Darren M. Chitty, Elizabeth F. Wanner, Rakhi Parmar, Peter R. Lewis:
Scaling ACO to large-scale vehicle fleet optimisation via partial-ACO. 97-98 - Chao Li, Jun Sun, Vasile Palade, Qidong Chen, Wei Fang:
Collaborative diversity control strategy for random drift particle swarm optimization. 99-100 - Muhammad Usman, AbuBakr Awad, Wei Pang, George M. Coghill:
Inferring structure and parameters of dynamic systems using particle swarm optimization. 101-102
Poster: Complex systems (artificial life/artificial immune systems/generative and developmental systems/evolutionary robotics/evolvable hardware)
- Dylan R. Ashley, Valliappa Chockalingam, Braedy Kuzma, Vadim Bulitko:
Learning to select mates in artificial life. 103-104 - Palina Bartashevich, Sanaz Mostaghim:
Positive impact of isomorphic changes in the environment on collective decision-making. 105-106 - Michal Bidlo:
Evolution of cellular automata development using various representations. 107-108 - Nicolas Bredèche:
HIT-EE: a novel embodied evolutionary algorithm for low cost swarm robotics. 109-110 - James Butterworth, Rahul Savani, Karl Tuyls:
Evolving indoor navigational strategies using gated recurrent units in NEAT. 111-112 - Anton V. Eremeev, Alexander V. Spirov:
Evaluation of runtime bounds for SELEX procedure with high selection pressure. 113-114 - Adam Gaier, Alexander Asteroth, Jean-Baptiste Mouret:
Are quality diversity algorithms better at generating stepping stones than objective-based search? 115-116 - Daniele Gravina, Antonios Liapis, Georgios N. Yannakakis:
Blending notions of diversity for MAP-elites. 117-118 - Djordje Grbic, Sebastian Risi:
Towards continual reinforcement learning through evolutionary meta-learning. 119-120 - Niels Justesen, Sebastian Risi, Jean-Baptiste Mouret:
MAP-Elites for noisy domains by adaptive sampling. 121-122 - Gongjin Lan, Jiunhan Chen, A. E. Eiben:
Evolutionary predator-prey robot systems: from simulation to real world. 123-124 - Alexander Furman, Danielle Nagar, Geoff Nitschke:
The cost of morphological complexity. 125-126 - Frank Veenstra, Emma Hart, Edgar Buchanan, Wei Li, Matteo De Carlo, Ágoston E. Eiben:
Comparing encodings for performance and phenotypic exploration in evolving modular robots. 127-128
Poster: Digital entertainment technologies and arts
- Martyn Amos, Matthew Crossley, Huw Lloyd:
Solving nurikabe with ant colony optimization. 129-130 - Alexander E. I. Brownlee, Suk-Jun Kim, Szu-Han Wang, Stella Chan, Jamie A. Lawson:
Crowd-sourcing the sounds of places with a web-based evolutionary algorithm. 131-132 - Laura Calle, Juan Julián Merelo Guervós, Antonio Mora García, Mario García Valdez:
Improved free form evolution for angry birds structures. 133-134 - Paul Cohen, Geoff Nitschke:
Evolving music with emotional feedback. 135-136
Poster: Evolutionary combinatorial optimization and metaheuristics
- Mateusz Slazynski, Salvador Abreu, Grzegorz J. Nalepa:
Towards a formal specification of local search neighborhoods from a constraint satisfaction problem structure. 137-138 - Aishwaryaprajna, Jonathan E. Rowe:
Noisy combinatorial optimisation by evolutionary algorithms. 139-140 - Etor Arza, Josu Ceberio, Aritz Pérez, Ekhine Irurozki:
Approaching the quadratic assignment problem with kernels of mallows models under the hamming distance. 141-142 - Abdelhakim Cheriet, Roberto Santana:
Optimizing permutation-based problems with a discrete vine-copula as a model for EDA. 143-144 - Aldy Gunawan, Vincent F. Yu, Audrey Tedja Widjaja, Pieter Vansteenwegen:
Simulated annealing for the single-vehicle cyclic inventory routing problem. 145-146 - Thomas E. Kent, Arthur G. Richards:
Decentralised multi-demic evolutionary approach to the dynamic multi-agent travelling salesman problem. 147-148 - Algirdas Lancinskas, Julius Zilinskas, Pascual Fernández, Blas Pelegrín:
Ranking-based discrete optimization algorithm for asymmetric competitive facility location. 149-150 - Luca Manzoni, Luca Mariot, Eva Tuba:
Does constraining the search space of GA always help?: the case of balanced crossover operators. 151-152 - Radomil Matousek, Ladislav Dobrovsky, Jakub Kudela:
The quadratic assignment problem: metaheuristic optimization using HC12 algorithm. 153-154 - Soheila Sadeghiram, Hui Ma, Gang Chen:
A memetic algorithm with distance-guided crossover: distributed data-intensive web service composition. 155-156
Poster: Evolutionary machine learning
- Mohammed Alshahrani, Spyridon Samothrakis, Maria Fasli:
Identifying idealised vectors for emotion detection using CMA-ES. 157-158 - Kumar Ayush, Abhishek Sinha:
Improving classification performance of support vector machines via guided custom kernel search. 159-160 - Qi Chen, Bing Xue, Mengjie Zhang:
Differential evolution for instance based transfer learning in genetic programming for symbolic regression. 161-162 - João Correia, Tiago Martins, Penousal Machado:
Evolutionary data augmentation in deep face detection. 163-164 - Wojciech Dudzik, Michal Kawulok, Jakub Nalepa:
Evolutionarily-tuned support vector machines. 165-166 - Gianluigi Folino, Francesco Sergio Pisani, Luigi Pontieri, Pietro Sabatino, Maryam Amir Haeri:
Using genetic programming for combining an ensemble of local and global outlier algorithms to detect new attacks. 167-168 - Aavaas Gajurel, Sushil J. Louis:
Multiobjective multi unit-type neuroevolution for micro in RTS games. 169-170 - Marketa Illetskova, Islam El-Nabarawy, Leonardo Enzo Brito da Silva, Daniel R. Tauritz, Donald C. Wunsch II:
Nested monte carlo search expression discovery for the automated design of fuzzy ART category choice functions. 171-172 - Ethan C. Jackson, Mark Daley:
Novelty search for deep reinforcement learning policy network weights by action sequence edit metric distance. 173-174 - Krzysztof Jurczuk, Marcin Czajkowski, Marek Kretowski:
Multi-GPU approach for big data mining: global induction of decision trees. 175-176 - Douglas Kirkpatrick, Arend Hintze:
Augmenting neuro-evolutionary adaptation with representations does not incur a speed accuracy trade-off. 177-178 - Ricardo Henrique Remes de Lima, Aurora T. R. Pozo:
Evolving convolutional neural networks through grammatical evolution. 179-180 - Marcus Märtens, Dario Izzo:
Neural network architecture search with differentiable cartesian genetic programming for regression. 181-182 - Masaya Nakata, Will Neil Browne:
How XCS can prevent misdistinguishing rule accuracy: a preliminary study. 183-184 - Patryk Orzechowski, Jason H. Moore:
Strategies for improving performance of evolutionary biclustering algorithm EBIC. 185-186 - Wenbin Pei, Bing Xue, Lin Shang, Mengjie Zhang:
Reuse of program trees in genetic programming with a new fitness function in high-dimensional unbalanced classification. 187-188 - Joshua Sirota, Vadim Bulitko, Matthew R. G. Brown, Sergio Poo Hernandez:
Evolving recurrent neural networks for emergent communication. 189-190 - Hao Wang, Thomas Bäck, Aske Plaat, Michael Emmerich, Mike Preuss:
On the potential of evolution strategies for neural network weight optimization. 191-192
Poster: Evolutionary multiobjective optimization
- Abdulaziz Alashaikh, Eisa Alanazi:
Preference-based multiobjective virtual machine placement: a ceteris paribus approach. 193-194 - AbuBakr Awad, Muhammad Usman, David Lusseau, George M. Coghill, Wei Pang:
A physarum-inspired competition algorithm for solving discrete multi-objective optimization problems. 195-196 - Christina Brester, Ivan Ryzhikov, Eugene Semenkin, Mikko Kolehmainen:
On a restart metaheuristic for real-valued multi-objective evolutionary algorithms. 197-198 - Jessica Finocchiaro, H. David Mathias:
Evolving cooperation for the iterated prisoner's dilemma. 199-200 - Ahsanul Habib, Hemant Kumar Singh, Tapabrata Ray:
A component-wise study of K-RVEA: observations and potential future developments. 201-202 - Haithem Hafsi, Hamza Gharsellaoui, Sadok Bouamama:
Towards a novel NSGA-II-based approach for multi-objective scientific workflow scheduling on hybrid clouds. 203-204 - Mardé Helbig, Heiner Zille, Mahrokh Javadi, Sanaz Mostaghim:
Performance of dynamic algorithms on the dynamic distance minimization problem. 205-206 - Carlos Ignacio Hernández Castellanos, Sina Ober-Blöbaum:
A decomposition-based EMOA for set-based robustness. 207-208 - Tatsumasa Ishikawa, Hiroaki Fukumoto, Akira Oyama, Hiroyuki Nishida:
Improved binary additive epsilon indicator for obtaining uniformly distributed solutions in multi-objective optimization. 209-210 - Mahrokh Javadi, Heiner Zille, Sanaz Mostaghim:
Modified crowding distance and mutation for multimodal multi-objective optimization. 211-212 - Adán José García, Julia Handl, Wilfrido Gómez-Flores, Mario Garza-Fabre:
Many-view clustering: an illustration using multiple dissimilarity measures. 213-214 - Yuri Cossich Lavinas, Claus Aranha, Tetsuya Sakurai:
Using diversity as a priority function for resource allocation on MOEA/D. 215-216 - Anna Lavygina, Kristopher Welsh, Alan Crispin:
On fairness as a rostering objective. 217-218 - Juhee Lim, Jongsoo Lee:
Reliability-based MOGA design optimization using probabilistic response surface method and bayesian neural network. 219-220 - Yijun Liu, Xin Li, Qijia Hao:
A new constrained multi-objective optimization problems algorithm based on group-sorting. 221-222 - Oskar Marko, Dejan Pavlovic, Vladimir S. Crnojevic, Kalyanmoy Deb:
Optimisation of crop configuration using NSGA-III with categorical genetic operators. 223-224 - Luis Miguel Antonio, Carlos A. Coello Coello, Silvia B. González-Brambila, Josué Figueroa González, Ma. Guadalupe Castillo Tapia:
Operational decomposition for large scale multi-objective optimization problems. 225-226 - Hugo Monzón, Hernán E. Aguirre, Sébastien Vérel, Arnaud Liefooghe, Bilel Derbel, Kiyoshi Tanaka:
Studying com partmental models interpolation to estimate MOEAs population size. 227-228 - Alberto Rodríguez Sánchez, Antonin Ponsich, Antonio López Jaimes:
Generation techniques and a novel on-line adaptation strategy for weight vectors within decomposition-based MOEAs. 229-230 - Hormoz Shahrzad, Babak Hodjat, Camille Dollé, Andrei Denissov, Simon Lau, Donn Goodhew, Justin Dyer, Risto Miikkulainen:
Enhanced optimization with composite objectives and novelty pulsation. 231-232 - Hemant Kumar Singh, Kalyanmoy Deb:
A parametric investigation of PBI and AASF scalarizations. 233-234 - Classical MOEAs for solving a multi-objective problem of supply chain design and operation. 235-236