Table of Contents

• Monitoring of drinking-water quality by means of a multi-objective ensemble learning approachVictor Henrique Alves Ribeiro, Gilberto Reynoso-Meza. 1-2 [doi]
• Self-organizing migrating algorithm for the 100-digit challengeQuoc Bao Diep, Ivan Zelinka, Swagatam Das. 3-4 [doi]
• L-SHADE with an adaptive penalty method of balancing the objective value and the constraint violationTakeshi Kawachi, Jun-ichi Kushida, Akira Hara, Tetsuyuki Takahama. 5-6 [doi]
• Hybrid-adaptive differential evolution with decay function (HyDE-DF) applied to the 100-digit challenge competition on single objective numerical optimizationFernando Lezama, João P. Soares, Ricardo Faia, Zita A. Vale. 7-8 [doi]
• Helper and equivalent objective different evolution for constrained optimisationTao Xu, Jun He 0004, Changjing Shang. 9-10 [doi]
• 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) 2019Ales Zamuda. 11-12 [doi]
• CUMDANCauchy-C1: a cellular EDA designed to solve the energy resource management problem under uncertaintyYoan Martínez López, Ansel Y. Rodríguez González, Julio Madera Quintana, Alexis Moya, Bismay Morgado, Miguel Betancourt Mayedo. 13-14 [doi]
• legends of the three kingdoms based on hierarchical macro strategy modelYoujie Zhang, Xiang Ding, Zhi Chen. 15-16 [doi]
• Gaussian process surrogate models for the CMA-ESLukás Bajer, Zbynek Pitra, Jakub Repický, Martin Holena. 17-18 [doi]
• Combining artificial neural networks and evolution to solve multiobjective knapsack problemsRoman Denysiuk, António Gaspar-Cunha, Alexandre C. B. Delbem. 19-20 [doi]
• Understanding exploration and exploitation powers of meta-heuristic stochastic optimization algorithms through statistical analysisTome Eftimov, Peter Korosec. 21-22 [doi]
• Generating interpretable reinforcement learning policies using genetic programmingDaniel Hein 0001, Steffen Udluft, Thomas A. Runkler. 23-24 [doi]
• n is efficient on monotone functions: an entropy compression argument. (hot-off-the-press track at GECCO 2019)Johannes Lengler, Anders Martinsson, Angelika Steger. 25-26 [doi]
• Low-Dimensional euclidean embedding for visualization of search spaces in combinatorial optimizationKrzysztof Michalak. 27-28 [doi]
• Discovering test statistics using genetic programmingJason H. Moore, Randal S. Olson, Yong Chen, Moshe Sipper. 29-30 [doi]
• EBIC: a scalable biclustering method for large scale data analysisPatryk Orzechowski, Jason H. Moore. 31-32 [doi]
• A bi-level hybrid PSO: MIP solver approach to define dynamic tariffs and estimate bounds for an electricity retailer profitInês Soares, Maria João Alves, Carlos Henggeler Antunes. 33-34 [doi]
• Stochastic program synthesis via recursion schemesJerry Swan, Krzysztof Krawiec, Zoltan A. Kocsis. 35-36 [doi]
• Analysing heuristic subsequences for offline hyper-heuristic learningWilliam B. Yates, Edward C. Keedwell. 37-38 [doi]
• Hot off the press in expert systems on underwater robotic missions: success history applied to differential evolution for underwater glider path planningAles Zamuda, José Daniel Hernández Sosa. 39-40 [doi]
• A two-phase genetic algorithm for incorporating environmental considerations with production, inventory and routing decisions in supply chain networksNader Azad, Adel Aazami, Ali Papi, Armin Jabbarzadeh. 41-42 [doi]
• Application of estimation of distribution algorithm for feature selectionMayowa Ayodele. 43-44 [doi]
• Hybrid estimation of distribution algorithm for solving a resource level allocation problem in a legal businessMayowa Ayodele, K. Nadia Papamichail, Geraldine Gallagher, Darren Buckley. 45-46 [doi]
• Beyond coreset discovery: evolutionary archetypesPietro Barbiero, Giovanni Squillero, Alberto Paolo Tonda. 47-48 [doi]
• Genetic algorithms are very good solved sudoku generatorsAmit Benbassat. 49-50 [doi]
• Stabilized training of generative adversarial networks by a genetic algorithmHwi-Yeon Cho, Yong-Hyuk Kim. 51-52 [doi]
• Determination of microscopic residual stresses using diffraction methods, EBSD maps, and evolutionary algorithmsJosé Ignacio Hidalgo, Ricardo Fernández, Oscar Garnica, J. Manuel Colmenar, Juan Lanchares, Gaspar González-Doncel. 53-54 [doi]
• Skill emergence and transfer in multi-agent environmentsIngmar Kanitscheider, Bowen Baker, Todor Markov, Igor Mordatch. 55-56 [doi]
• Modelling and solving the combined inventory routing problem with risk considerationAhmed Kheiri, Konstantinos Zografos. 57-58 [doi]
• Integrating agent actions with genetic action sequence methodMan-Je Kim, Jun Suk Kim, Donghyeon Lee, Sungjin James Kim, Min-Jung Kim, Chang Wook Ahn. 59-60 [doi]
• Predictive model for epistasis-based basis evaluation on pseudo-boolean function using deep neural networksYong Hoon Kim, Junghwan Lee, Yong-Hyuk Kim. 61-62 [doi]
• Parallel GPQUICKWilliam B. Langdon. 63-64 [doi]
• Genetic algorithm-based feature selection for depression scale predictionSeung-Ju Lee, Hyun-Ji Moon, Da-jung Kim, Yourim Yoon. 65-66 [doi]
• Multidimensional time series feature engineering by hybrid evolutionary approachPiotr Lipinski, Krzysztof Michalak. 67-68 [doi]
• CE+EPSO: a merged approach to solve SCOPF problemCarolina Gil Marcelino, Carlos E. Pedreira, Elizabeth F. Wanner, Leonel M. Carvalho, Vladimiro Miranda, Armando L. da Silva. 69-70 [doi]
• On the automatic planning of healthy and balanced menusAlejandro Marrero, Eduardo Segredo, Coromoto León. 71-72 [doi]
• EDA with hamming distance for consumption-loan planning in experimental economicsYukiko Orito, Tomoko Kashima. 73-74 [doi]
• Towards solving neural networks with optimization trajectory searchLia T. Parsenadze, Danilo Vasconcellos Vargas, Toshiyuki Fujita. 75-76 [doi]
• A honeybee mating optimization algorithm for solving the static bike rebalancing problemMariem Sebai, Ezzeddine Fatnassi, Lilia Rejeb. 77-78 [doi]
• OINNIONN: outward inward neural network and inward outward neural network evolutionAviv Segev, Rituparna Datta, Ryan Benton, Dorothy Curtis. 79-80 [doi]
• Techniques from evolutionary computation to implement as experimental approaches in synthetic biology: tests in silicoAlexander V. Spirov, Ekaterina M. Myasnikova. 81-82 [doi]
• Selective pressure in constrained differential evolutionVladimir Stanovov, Shakhnaz Akhmedova, Eugene Semenkin. 83-84 [doi]
• Trajectory optimization for car races using genetic algorithmsDana Vrajitoru. 85-86 [doi]
• Probabilistic grammar-based deep neuroevolutionPak-Kan Wong, Man Leung Wong, Kwong-Sak Leung. 87-88 [doi]
• Identifying variable interaction using mutual information of multiple local optimaYapei Wu, Xingguang Peng, Demin Xu. 89-90 [doi]
• Predictability on performance of surrogate-assisted evolutionary algorithm according to problem dimensionDong-Pil Yu, Yong-Hyuk Kim. 91-92 [doi]
• Bi-objective optimal planning for emergency resource allocation in the maritime oil spill accident response phase under uncertaintyGuohai Zhu, Kewei Yang, Qingsong Zhao, Zhiwei Yang. 93-94 [doi]
• A new hybrid ant colony algorithms for the traveling thief problemWiem Zouari, Inès Alaya, Moncef Tagina. 95-96 [doi]
• Scaling ACO to large-scale vehicle fleet optimisation via partial-ACODarren M. Chitty, Elizabeth Wanner, Rakhi Parmar, Peter R. Lewis. 97-98 [doi]
• Collaborative diversity control strategy for random drift particle swarm optimizationChao Li, Jun Sun, Vasile Palade, Qidong Chen, Wei Fang. 99-100 [doi]
• Inferring structure and parameters of dynamic systems using particle swarm optimizationMuhammad Usman, AbuBakr Awad, Wei Pang, George M. Coghill. 101-102 [doi]
• Learning to select mates in artificial lifeDylan R. Ashley, Valliappa Chockalingam, Braedy Kuzma, Vadim Bulitko. 103-104 [doi]
• Positive impact of isomorphic changes in the environment on collective decision-makingPalina Bartashevich, Sanaz Mostaghim. 105-106 [doi]
• Evolution of cellular automata development using various representationsMichal Bidlo. 107-108 [doi]
• HIT-EE: a novel embodied evolutionary algorithm for low cost swarm roboticsNicolas Bredèche. 109-110 [doi]
• Evolving indoor navigational strategies using gated recurrent units in NEATJames Butterworth, Rahul Savani, Karl Tuyls. 111-112 [doi]
• Evaluation of runtime bounds for SELEX procedure with high selection pressureAnton V. Eremeev, Alexander V. Spirov. 113-114 [doi]
• Are quality diversity algorithms better at generating stepping stones than objective-based search?Adam Gaier, Alexander Asteroth, Jean-Baptiste Mouret. 115-116 [doi]
• Blending notions of diversity for MAP-elitesDaniele Gravina, Antonios Liapis, Georgios N. Yannakakis. 117-118 [doi]
• Towards continual reinforcement learning through evolutionary meta-learningDjordje Grbic, Sebastian Risi. 119-120 [doi]
• MAP-Elites for noisy domains by adaptive samplingNiels Justesen, Sebastian Risi, Jean-Baptiste Mouret. 121-122 [doi]
• Evolutionary predator-prey robot systems: from simulation to real worldGongjin Lan, Jiunhan Chen, A. E. Eiben. 123-124 [doi]
• The cost of morphological complexityAlexander Furman, Danielle Nagar, Geoff Nitschke. 125-126 [doi]
• Comparing encodings for performance and phenotypic exploration in evolving modular robotsFrank Veenstra, Emma Hart, Edgar Buchanan, Wei Li, Matteo De Carlo, Agoston E. Eiben. 127-128 [doi]
• Solving nurikabe with ant colony optimizationMartyn Amos, Matthew Crossley, Huw Lloyd. 129-130 [doi]
• Crowd-sourcing the sounds of places with a web-based evolutionary algorithmAlexander E. I. Brownlee, Suk-Jun Kim, Szu-Han Wang, Stella Chan, Jamie A. Lawson. 131-132 [doi]
• Improved free form evolution for angry birds structuresLaura Calle, Juan Julián Merelo Guervós, Antonio Mora García, Mario García Valdez. 133-134 [doi]
• Evolving music with emotional feedbackPaul Cohen, Geoff Nitschke. 135-136 [doi]
• Towards a formal specification of local search neighborhoods from a constraint satisfaction problem structureMateusz Slazynski, Salvador Abreu, Grzegorz J. Nalepa. 137-138 [doi]
• Noisy combinatorial optimisation by evolutionary algorithmsAishwaryaprajna, Jonathan E. Rowe. 139-140 [doi]
• Approaching the quadratic assignment problem with kernels of mallows models under the hamming distanceEtor Arza, Josu Ceberio, Aritz Pérez, Ekhine Irurozki. 141-142 [doi]
• Optimizing permutation-based problems with a discrete vine-copula as a model for EDAAbdelhakim Cheriet, Roberto Santana. 143-144 [doi]
• Simulated annealing for the single-vehicle cyclic inventory routing problemAldy Gunawan, Vincent F. Yu, Audrey Tedja Widjaja, Pieter Vansteenwegen. 145-146 [doi]
• Decentralised multi-demic evolutionary approach to the dynamic multi-agent travelling salesman problemThomas E. Kent, Arthur G. Richards. 147-148 [doi]
• Ranking-based discrete optimization algorithm for asymmetric competitive facility locationAlgirdas Lancinskas, Julius Zilinskas, Pascual Fernández, Blas Pelegrín. 149-150 [doi]
• Does constraining the search space of GA always help?: the case of balanced crossover operatorsLuca Manzoni, Luca Mariot, Eva Tuba. 151-152 [doi]
• The quadratic assignment problem: metaheuristic optimization using HC12 algorithmRadomil Matousek, Ladislav Dobrovsky, Jakub Kudela. 153-154 [doi]
• A memetic algorithm with distance-guided crossover: distributed data-intensive web service compositionSoheila Sadeghiram, Hui Ma 0001, Gang Chen 0002. 155-156 [doi]
• Identifying idealised vectors for emotion detection using CMA-ESMohammed Alshahrani, Spyridon Samothrakis, Maria Fasli. 157-158 [doi]
• Improving classification performance of support vector machines via guided custom kernel searchKumar Ayush, Abhishek Sinha. 159-160 [doi]
• Differential evolution for instance based transfer learning in genetic programming for symbolic regressionQi Chen 0002, Bing Xue 0001, Mengjie Zhang. 161-162 [doi]
• Evolutionary data augmentation in deep face detectionJoão Correia, Tiago Martins, Penousal Machado. 163-164 [doi]
• Evolutionarily-tuned support vector machinesWojciech Dudzik, Michal Kawulok, Jakub Nalepa. 165-166 [doi]
• Using genetic programming for combining an ensemble of local and global outlier algorithms to detect new attacksGianluigi Folino, Francesco Sergio Pisani, Luigi Pontieri, Pietro Sabatino, Maryam Amir Haeri. 167-168 [doi]
• Multiobjective multi unit-type neuroevolution for micro in RTS gamesAavaas Gajurel, Sushil J. Louis. 169-170 [doi]
• Nested monte carlo search expression discovery for the automated design of fuzzy ART category choice functionsMarketa Illetskova, Islam El-Nabarawy, Leonardo Enzo Brito da Silva, Daniel R. Tauritz, Donald C. Wunsch II. 171-172 [doi]
• Novelty search for deep reinforcement learning policy network weights by action sequence edit metric distanceEthan C. Jackson, Mark Daley. 173-174 [doi]
• Multi-GPU approach for big data mining: global induction of decision treesKrzysztof Jurczuk, Marcin Czajkowski, Marek Kretowski. 175-176 [doi]
• Augmenting neuro-evolutionary adaptation with representations does not incur a speed accuracy trade-offDouglas Kirkpatrick, Arend Hintze. 177-178 [doi]
• Evolving convolutional neural networks through grammatical evolutionRicardo H. R. Lima, Aurora T. R. Pozo. 179-180 [doi]
• Neural network architecture search with differentiable cartesian genetic programming for regressionMarcus Märtens, Dario Izzo. 181-182 [doi]
• How XCS can prevent misdistinguishing rule accuracy: a preliminary studyMasaya Nakata, Will Neil Browne. 183-184 [doi]
• Strategies for improving performance of evolutionary biclustering algorithm EBICPatryk Orzechowski, Jason H. Moore. 185-186 [doi]
• Reuse of program trees in genetic programming with a new fitness function in high-dimensional unbalanced classificationWenBin Pei, Bing Xue 0001, Lin Shang, Mengjie Zhang. 187-188 [doi]
• Evolving recurrent neural networks for emergent communicationJoshua Sirota, Vadim Bulitko, Matthew R. G. Brown, Sergio Poo Hernandez. 189-190 [doi]
• On the potential of evolution strategies for neural network weight optimizationHao Wang 0025, Thomas Bäck, Aske Plaat, Michael Emmerich, Mike Preuss. 191-192 [doi]
• Preference-based multiobjective virtual machine placement: a ceteris paribus approachAbdulaziz Alashaikh, Eisa Alanazi. 193-194 [doi]
• A physarum-inspired competition algorithm for solving discrete multi-objective optimization problemsAbuBakr Awad, Muhammad Usman, David Lusseau, George M. Coghill, Wei Pang. 195-196 [doi]
• On a restart metaheuristic for real-valued multi-objective evolutionary algorithmsChristina Brester, Ivan Ryzhikov, Eugene Semenkin, Mikko Kolehmainen. 197-198 [doi]
• Evolving cooperation for the iterated prisoner's dilemmaJessica Finocchiaro, H. David Mathias. 199-200 [doi]
• A component-wise study of K-RVEA: observations and potential future developmentsAhsanul Habib, Hemant Kumar Singh, Tapabrata Ray. 201-202 [doi]
• Towards a novel NSGA-II-based approach for multi-objective scientific workflow scheduling on hybrid cloudsHaithem Hafsi, Hamza Gharsellaoui, Sadok Bouamama. 203-204 [doi]
• Performance of dynamic algorithms on the dynamic distance minimization problemMardé Heibig, Heiner Zille, Mahrokh Javadi, Sanaz Mostaghim. 205-206 [doi]
• A decomposition-based EMOA for set-based robustnessCarlos Ignacio Hernández Castellanos, Sina Ober-Blöbaum. 207-208 [doi]
• Improved binary additive epsilon indicator for obtaining uniformly distributed solutions in multi-objective optimizationTatsumasa Ishikawa, Hiroaki Fukumoto, Akira Oyama, Hiroyuki Nishida. 209-210 [doi]
• Modified crowding distance and mutation for multimodal multi-objective optimizationMahrokh Javadi, Heiner Zille, Sanaz Mostaghim. 211-212 [doi]
• Many-view clustering: an illustration using multiple dissimilarity measuresAdán José García, Julia Handl, Wilfrido Gómez-Flores, Mario Garza-Fabre. 213-214 [doi]
• Using diversity as a priority function for resource allocation on MOEA/DYuri Cossich Lavinas, Claus Aranha, Tetsuya Sakurai. 215-216 [doi]
• On fairness as a rostering objectiveAnna Lavygina, Kristopher Welsh, Alan Crispin. 217-218 [doi]
• Reliability-based MOGA design optimization using probabilistic response surface method and bayesian neural networkJuhee Lim, Jongsoo Lee. 219-220 [doi]
• A new constrained multi-objective optimization problems algorithm based on group-sortingYijun Liu, Xin Li, Qijia Hao. 221-222 [doi]
• Optimisation of crop configuration using NSGA-III with categorical genetic operatorsOskar Marko, Dejan Pavlovic, Vladimir S. Crnojevic, Kalyanmoy Deb. 223-224 [doi]
• Operational decomposition for large scale multi-objective optimization problemsLuis Miguel Antonio, Carlos A. Coello Coello, Silvia B. González-Brambila, Josué Figueroa González, Ma. Guadalupe Castillo Tapia. 225-226 [doi]
• Studying com partmental models interpolation to estimate MOEAs population sizeHugo Monzón, Hernán E. Aguirre, Sébastien Vérel, Arnaud Liefooghe, Bilel Derbel, Kiyoshi Tanaka. 227-228 [doi]
• Generation techniques and a novel on-line adaptation strategy for weight vectors within decomposition-based MOEAsAlberto Rodríguez Sánchez, Antonin Ponsich, Antonio López Jaimes. 229-230 [doi]
• Enhanced optimization with composite objectives and novelty pulsationHormoz Shahrzad, Babak Hodjat, Camille Dollé, Andrei Denissov, Simon Lau, Donn Goodhew, Justin Dyer, Risto Miikkulainen. 231-232 [doi]
• A parametric investigation of PBI and AASF scalarizationsHemant Kumar Singh, Kalyanmoy Deb. 233-234 [doi]
• Classical MOEAs for solving a multi-objective problem of supply chain design and operation235-236 [doi]
• Balancing exploration and exploitation in multiobjective batch bayesian optimizationHongyan Wang, Hua Xu, Yuan Yuan, Xiaomin Sun, Junhui Deng. 237-238 [doi]
• Noisy multiobjective black-box optimization using bayesian optimizationHongyan Wang, Hua Xu, Yuan Yuan, Junhui Deng, Xiaomin Sun. 239-240 [doi]
• α-dominanceGuo Yu, Yaochu Jin, Markus Olhofer. 241-242 [doi]
• Solving optimization problems with high conditioning by means of online whiteningSamineh Bagheri, Wolfgang Konen, Thomas Bäck. 243-244 [doi]
• Exploitation of multiple surrogate models in multi-point infill sampling strategiesPaul Beaucaire, Charlotte Beauthier, Caroline Sainvitu. 245-246 [doi]
• On equivalence of algorithm's implementations: the CMA-ES algorithm and its five implementationsRafal Biedrzycki. 247-248 [doi]
• Comparing reliability of grid-based quality-diversity algorithms using artificial landscapesLeo Cazenille. 249-250 [doi]
• Empirical evaluation of contextual policy search with a comparison-based surrogate model and active covariance matrix adaptationAlexander Fabisch. 251-252 [doi]
• Evaluating MAP-Elites on constrained optimization problemsStefano Fioravanzo, Giovanni Iacca. 253-254 [doi]
• A new neighborhood topology for QUAntum particle swarm optimization (QUAPSO)Arnauci Flori, Hamouche Oulhadj, Patrick Siarry. 255-256 [doi]
• Extended stochastic derivative-free optimization on riemannian manifoldsRobert Simon Fong, Peter Tiño. 257-258 [doi]
• An analysis of control parameters of copula-based EDA algorithm with model migrationMartin Hyrs, Josef Schwarz. 259-260 [doi]
• Limitations of benchmark sets and landscape features for algorithm selection and performance predictionBenjamin Lacroix, John A. W. McCall. 261-262 [doi]
• On the use of metaheuristics in hyperparameters optimization of gaussian processesPramudita Satria Palar, Lavi Rizki Zuhal, Koji Shimoyama. 263-264 [doi]
• On the non-convergence of differential evolution: some generalized adversarial conditions and a remedyDebolina Paul, Saptarshi Chakraborty, Swagatam Das, Ivan Zelinka. 265-266 [doi]
• Openly revisiting derivative-free optimizationJérémy Rapin, Pauline Dorval, Jules Pondard, Nicolas Vasilache, Marie-Liesse Cauwet, Camille Couprie, Olivier Teytaud. 267-268 [doi]
• Investigating the effects of population size and the number of subcomponents on the performance of SHADE algorithm with random adaptive grouping for LSGO problemsEvgenii Sopov, Alexey Vakhnin. 269-270 [doi]
• Benchmarking the region learning-based JADE on noiseless functionsMingcheng Zuo, Guangming Dai, Lei Peng, Maocai Wang, Pan Peng, Changchun Chen. 271-272 [doi]
• A new mutation operator with the ability to adjust exploration and exploitation for DE algorithmMingcheng Zuo, Guangming Dai, Lei Peng, Maocai Wang, Pan Peng, Changchun Chen. 273-274 [doi]
• GECCO black-box optimization competitions: progress from 2009 to 2018Urban Skvorc, Tome Eftimov, Peter Korosec. 275-276 [doi]
• λ, λ)) GAAnton Bassin, Maxim Buzdalov. 277-278 [doi]
• Approximate search in dissimilarity spaces using GADavid Bernhauer, Tomás Skopal. 279-280 [doi]
• A parallel multi-population biased random-key genetic algorithm for electric distribution network reconfigurationHaroldo de Faria Jr., Willian Tessaro Lunardi, Holger Voos. 281-282 [doi]
• Genealogical patterns in evolutionary algorithmsCarlos M. Fernandes, Agostinho C. Rosa, Juan Luis Jiménez Laredo, Juan Julián Merelo Guervós. 283-284 [doi]
• A change would do you good: GA-Based approach for hiding data in program executablesRyan Gabrys, Luis Martinez. 285-286 [doi]
• A BRKGA for the integrated scheduling problem in FMSsS. Mahdi Homayouni, Dalila B. M. M. Fontes, Fernando A. C. C. Fontes. 287-288 [doi]
• Parameter-less, population-sizing DSMGA-IIMarcin M. Komarnicki, Michal Witold Przewozniczek. 289-290 [doi]
• Genetic algorithms as shrinkers in property-based testingFang-Yi Lo, Chao-Hong Chen, Ying-Ping Chen. 291-292 [doi]
• Runtime analysis of abstract evolutionary search with standard crossoverTina Malalanirainy, Alberto Moraglio. 293-294 [doi]
• Latin hypercube initialization strategy for design space exploration of deep neural network architecturesHeitor R. Medeiros, Diogo M. F. Izidio, Antonyus P. Do A. Ferreira, Edna Natividade da Silva Barros. 295-296 [doi]
• Multiple world genetic algorithm to analyze individually advantageous behaviors in complex networksYutaro Miura, Fujio Toriumi, Toshiharu Sugawara. 297-298 [doi]
• A study of the levy distribution in generation of BRKGA random keys applied to global optimizationMariana Moura, Ricardo Silva. 299 [doi]
• A probabilistic bitwise genetic algorithm for B-spline based image deformation estimationTakumi Nakane, Takuya Akashi, Xuequan Lu, Chao Zhang. 300-301 [doi]
• A group work inspired generation alternation model of real-coded GATakatoshi Niwa, Koya Ihara, Shohei Kato. 302-303 [doi]
• Mining a massive RNA-seq dataset with biclustering: are evolutionary approaches ready for big data?Patryk Orzechowski, Jason H. Moore. 304-305 [doi]
• Island model for parallel evolutionary optimization of spiking neuromorphic computingCatherine D. Schuman, James S. Plank, Robert M. Patton, Thomas E. Potok. 306-307 [doi]
• Evolving to recognize high-dimensional relationships in data: GA operators and representation designed expressly for community detectionKenneth Smith, Cezary Z. Janikow, Sharlee Climer. 308-309 [doi]
• Comparison of GAs in black-box scenariosCheng-Hao Yang, Hou-Teng Cheong, Tian-Li Yu. 310-311 [doi]
• Parameter-less population pyramid with automatic feedbackAdam M. Zielinski, Marcin M. Komarnicki, Michal Witold Przewozniczek. 312-313 [doi]
• AlphaStar: an evolutionary computation perspectiveKai Arulkumaran, Antoine Cully, Julian Togelius. 314-315 [doi]
• Evolved cellular automata for edge detectionAlina Enescu, Anca Andreica, Laura Diosan. 316-317 [doi]
• Can route planning be smarter with transfer optimization?Ray Lim, Yew-Soon Ong, Hanh Thi Hong Phan, Abhishek Gupta 0001, Nengsheng Allan Zhang. 318-319 [doi]
• Improving the algorithmic efficiency and performance of channel-based evolutionary algorithmsJuan Julián Merelo Guervós, Juan Luis Jiménez Laredo, Pedro A. Castillo, Mario García Valdez, Sergio Rojas Galeano. 320-321 [doi]
• Textonboost based on differential evolutionKeiko Ono, Daisuke Tawara, Yoshiko Hanada. 322-323 [doi]
• A hybrid between a surrogate-assisted evolutionary algorithm and a trust region method for constrained optimizationRommel G. Regis. 324-325 [doi]
• Comparing terminal sets for evolving CMA-ES mean-update selectionSamuel N. Richter, Michael G. Schoen, Daniel R. Tauritz. 326-327 [doi]
• A classification-based selection for evolutionary optimizationJinyuan Zhang, Jimmy Xiangji Huang, Qinmin Vivian Hu. 328-329 [doi]
• A population entropy based adaptation strategy for differential evolutionYanyun Zhang, Guangming Dai, Mingcheng Zuo, Lei Peng, Maocai Wang, Zhengquan Liu. 330-331 [doi]
• A genetic programming approach to feature selection and construction for ransomware, phishing and spam detectionHarith Al-Sahaf, Ian Welch. 332-333 [doi]
• Genetic programming hyper-heuristic with knowledge transfer for uncertain capacitated arc routing problemMazhar Ansari Ardeh, Yi Mei, Mengjie Zhang. 334-335 [doi]
• To adapt or not to adapt, or the beauty of random settingsJoão E. Batista, Nuno M. Rodrigues, Sara Silva. 336-337 [doi]
• Parsimony measures in multi-objective genetic programming for symbolic regressionBogdan Burlacu, Gabriel Kronberger, Michael Kommenda, Michael Affenzeller. 338-339 [doi]
• Increasing genetic programming robustness using simulated dunning-kruger effectThomas D. Griffiths, Anikó Ekárt. 340-341 [doi]
• Designing correlation immune boolean functions with minimal hamming weight using various genetic programming methodsJakub Husa. 342-343 [doi]
• Investigating the use of linear programming to solve implicit symbolic regression problemsQuang Nhat Huynh, Hemant Kumar Singh, Tapabrata Ray. 344-345 [doi]
• Tag-accessed memory for genetic programmingAlexander Lalejini, Charles Ofria. 346-347 [doi]
• Space partition based gene expression programming for symbolic regressionQiang Lu, Shuo Zhou, Fan Tao, Zhiguang Wang. 348-349 [doi]
• Transfer learning: a building block selection mechanism in genetic programming for symbolic regressionBrandon Muller, Harith Al-Sahaf, Bing Xue 0001, Mengjie Zhang. 350-351 [doi]
• Automated design of random dynamic graph models for enterprise computer network applicationsAaron Scott Pope, Daniel R. Tauritz, Chris Rawlings. 352-353 [doi]
• Semantic fitness function in genetic programming based on semantics flow analysisPak-Kan Wong, Man Leung Wong, Kwong-Sak Leung. 354-355 [doi]
• Multimodal genetic programming using program similarity measurement and its application to wall-following problemShubu Yoshida, Tomohiro Harada, Ruck Thawonmas. 356-357 [doi]
• Efficient frontiers in portfolio optimisation with minimum proportion constraintsTahani S. Alotaibi, Matthew J. Craven. 358-359 [doi]
• Genetic algorithms for the network slice design problem under uncertaintyThomas Bauschert, Varun S. Reddy. 360-361 [doi]
• Phoneme aware speech recognition through evolutionary optimisationJordan J. Bird, Elizabeth Wanner, Anikó Ekárt, Diego R. Faria. 362-363 [doi]
• Bond strength prediction of FRP-bar reinforced concrete: a multi-gene genetic programming approachHamed Bolandi, Wolfgang Banzhaf, Nizar Lajnef, Kaveh Barri, Amir Hossein Alavi. 364 [doi]
• Multi-objective genetic algorithms for reducing mark read-out effort in lithographic testsPierluigi Frisco, Timo Bootsma, Thomas Bäck. 365-366 [doi]
• A genetic algorithm based column generation method for multi-depot electric bus vehicle schedulingCongcong Guo, Chunlu Wang, Xingquan Zuo. 367-368 [doi]
• A genetic algorithm for multi-robot routing in automated bridge inspectionNicholas Harris, Siming Liu 0001, Sushil J. Louis, Jim Hung La. 369-370 [doi]
• On the use of context sensitive grammars in grammatical evolution for legal non-compliance detectionCarl Im, Erik Hemberg. 371-372 [doi]
• EvoIsland: immersive interactive evolutionary 3D modellingAlexander Ivanov, Christian Jacob 0001. 373-374 [doi]
• Optimal equipment assignment for oil spill response using a genetic algorithmHye-Jin Kim, Junghwan Lee, Jong-Hwui Yun, Yong-Hyuk Kim. 375-376 [doi]
• Impact of subcircuit selection on the efficiency of CGP-based optimization of gate-level circuitsJitka Kocnova, Zdenek Vasícek. 377-378 [doi]
• Discovery of robust protocols for secure quantum cryptographyWalter O. Krawec, Sam A. Markelon. 379-380 [doi]
• Enhancing classification performance of convolutional neural networks for prostate cancer detection on magnetic resonance images: a study with the semantic learning machinePaulo Lapa, Ivo Gonçalves, Leonardo Rundo, Mauro Castelli. 381-382 [doi]
• Evolving planar mechanisms for the conceptual stage of mechanical designPaul Lapok, Alistair Lawson, Ben Paechter. 383-384 [doi]
• Benchmarking genetic programming in dynamic insider threat detectionDuc C. Le, Malcolm I. Heywood, A. Nur Zincir-Heywood. 385-386 [doi]
• Multi-objective collective search and movement-based metrics in swarm roboticsSebastian Mai, Heiner Zille, Christoph Steup, Sanaz Mostaghim. 387-388 [doi]
• Evolutionary optimization of epidemic control strategies for livestock disease preventionKrzysztof Michalak. 389-390 [doi]
• Optimization of chemical structures for seawater desalinationKyo Migishima, Takahiro Fuji, Hernán E. Aguirre, Rodolfo Cruz-Silva, Kiyoshi Tanaka. 391-392 [doi]
• Evolving optimal sun-shading building façadesLeon Coetzee, Geoff Nitschke. 393-394 [doi]
• On the design of S-box constructions with genetic programmingStjepan Picek, Domagoj Jakobovic. 395-396 [doi]
• Solving the first and last mile problem with connected and autonomous vehiclesAlma As-Aad Rahat, Ralph Ledbetter, Alex Dawn, Robert Byrne, Richard Everson. 397-398 [doi]
• Feature selection for surrogate model-based optimizationFrederik Rehbach, Lorenzo Gentile, Thomas Bartz-Beielstein. 399-400 [doi]
• Evolutionary refinement of the 3D structure of multi-domain protein complexes from small angle X-ray scattering dataOlga Rudenko, Aurélien Thureau, Javier Perez. 401-402 [doi]
• Neural network-based multiomics data integration in Alzheimer's diseasePankhuri Singhal, Shefali S. Verma, Scott M. Dudek, Marylyn D. Ritchie. 403-404 [doi]
• Neural-network assistance to calculate precise eigenvalue for fitness evaluation of real product designYukito Tsunoda, Takahiro Notsu, Yasufumi Sakai, Naoki Hamada, Toshihiko Mori, Teruo Ishihara, Atsuki Inoue. 405-406 [doi]
• Graph-based multi-objective generation of customised wiring harnessesJens Weise, Steven Benkhardt, Sanaz Mostaghim. 407-408 [doi]
• Study on multi-objective optimization for the allocation of transit aircraft to gateway considering satellite hallBoyuan Xia, Zhiwei Yang, Qingsong Zhao. 409-410 [doi]
• Franken-swarm: grammatical evolution for the automatic generation of swarm-like meta-heuristicsAnna Bogdanova, Jair Pereira Junior, Claus Aranha. 411-412 [doi]
• Genetic improvement of data gives binary logarithm from sqrtWilliam B. Langdon, Justyna Petke. 413-414 [doi]
• Visualizing swarm behavior with a particle density mapHyeon Chang Lee, Yong-Hyuk Kim. 415-416 [doi]
• Security testing of web applications: a search-based approach for detecting SQL injection vulnerabilitiesMuyang Liu, Ke Li, Tao Chen. 417-418 [doi]
• Towards evolutionary theorem proving for isabelle/HOLYutaka Nagashima. 419-420 [doi]
• A memetic NSGA-II with EDA-based local search for fully automated multiobjective web service compositionChen Wang 0013, Hui Ma 0001, Gang Chen 0002, Sven Hartmann. 421-422 [doi]
• Black-box complexity of the binary value functionNina Bulanova, Maxim Buzdalov. 423-424 [doi]
• Maximizing drift is not optimal for solving OneMaxNathan Buskulic, Carola Doerr. 425-426 [doi]
• Unlimited budget analysisJun He 0004, Thomas Jansen 0001, Christine Zarges. 427-428 [doi]
• A mathematical analysis of EDAs with distance-based exponential modelsImanol Unanue, María Merino, José Antonio Lozano. 429-430 [doi]
• Evolutionary robotics tutorialNicolas Bredèche, Stéphane Doncieux, Jean-Baptiste Mouret. 431-460 [doi]
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• Evolutionary computation: a unified approachKenneth De Jong. 507-522 [doi]
• Theory for non-theoreticians: introductory tutorialBenjamin Doerr. 523-549 [doi]
• Neuroevolution for deep reinforcement learning problemsDavid Ha. 550-593 [doi]
• A practical guide to experimentation (and benchmarking)Nikolaus Hansen. 594-613 [doi]
• Evolutionary many-objective optimizationHisao Ishibuchi, Hiroyuki Sato. 614-661 [doi]
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• Evolution of neural networksRisto Miikkulainen. 694-709 [doi]
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• Model-based evolutionary algorithmsDirk Thierens, Peter A. N. Bosman. 806-836 [doi]
• CMA-ES and advanced adaptation mechanismsYouhei Akimoto, Nikolaus Hansen. 837-861 [doi]
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• Visualization in multiobjective optimizationBogdan Filipic, Tea Tusar. 951-974 [doi]
• Solving complex problems with coevolutionary algorithmsKrzysztof Krawiec, Malcolm I. Heywood. 975-1001 [doi]
• Decomposition multi-objective optimisation: current developments and future opportunitiesKe Li 0001, Qingfu Zhang 0001. 1002-1031 [doi]
• Semantic genetic programmingAlberto Moraglio, Krzysztof Krawiec. 1032-1055 [doi]
• Evolutionary computation for digital artAneta Neumann, Frank Neumann 0001. 1056-1076 [doi]
• Recent advances in fitness landscape analysisGabriela Ochoa, Katherine Malan. 1077-1094 [doi]
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• Next generation genetic algorithmsDarrell Whitley, Francisco Chicano, Gabriela Ochoa, Andrew M. Sutton, Renato Tinós. 1113-1136 [doi]
• Exploratory landscape analysisPascal Kerschke, Mike Preuss. 1137-1155 [doi]
• Creative evolutionary computationAntonios Liapis, Georgios N. Yannakakis. 1156-1171 [doi]
• Concurrency in evolutionary algorithmsJuan Julián Merelo Guervós. 1172-1174 [doi]
• Push: genetic programming for finite algebrasLee Spector, Nicholas Freitag McPhee, Lee Spector, David M. Clark, Ian Lindsay, Bradford Barr, Jon Klein. 1175-1196 [doi]
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• Evolutionary computation and evolutionary deep learning for image analysis, signal processing and pattern recognitionMengjie Zhang, Stefano Cagnoni. 1226-1251 [doi]
• Minimum spanning tree-based clustering of large pareto archivesAndrzej Jaszkiewicz. 1252-1253 [doi]
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• Predicting the remaining useful life of plasma equipment through XCSRLiang-Yu Chen, Jia-Hua Lee, Ya-Liang Yang, Ming-Tsung Yeh, Tzu-Chien Hsiao. 1263-1270 [doi]
• LCS-based automatic configuration of approximate computing parameters for FPGA system designsSimon Conrady, Manu Manuel, Arne Kreddig, Walter Stechele. 1271-1279 [doi]
• Real-time detection of internet addiction using reinforcement learning systemHong-Ming Ji, Liang-Yu Chen, Tzu-Chien Hsiao. 1280-1288 [doi]
• Preliminary tests of a real-valued anticipatory classifier systemNorbert Kozlowski, Olgierd Unold. 1289-1294 [doi]
• A survey of formal theoretical advances regarding XCSDavid Pätzel, Anthony Stein, Jörg Hähner. 1295-1302 [doi]
• XCS-CR for handling input, output, and reward noiseTakato Tatsumi, Keiki Takadama. 1303-1311 [doi]
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• Solving the parameterless firefighter problem using multiobjective evolutionary algorithmsKrzysztof Michalak. 1321-1328 [doi]
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• Evolutionary and swarm-intelligence algorithms through monadic compositionGary Pamparà, Andries P. Engelbrecht. 1382-1390 [doi]
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• Landscape analysis under measurement errorKhulood AlYahya, Ozgur E. Akman, Jonathan E. Fieldsend. 1415-1418 [doi]
• Coupling the design of benchmark with algorithm in landscape-aware solver designJohann Dréo, Carola Doerr, Yann Semet. 1419-1420 [doi]
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• Uncertainty in real-world steel stacking problemsAndreas Beham, Sebastian Raggl, Stefan Wagner 0002, Michael Affenzeller. 1438-1440 [doi]
• A generator for dynamically constrained optimization problemsGary Pamparà, Andries P. Engelbrecht. 1441-1448 [doi]
• Hybrid techniques for detecting changes in less detectable dynamic multiobjective optimization problemsShaaban Sahmoud, Haluk Rahmi Topcuoglu. 1449-1456 [doi]
• An intuitive and traceable human-based evolutionary computation system for solving problems in human organizationsKei Ohnishi, Tomohiro Yoshikawa, Tian-Li Yu. 1457-1464 [doi]
• Human-evolutionary problem solving through gamification of a bin-packing problemNicholas D. F. Ross, Matthew Barrie Johns, Edward C. Keedwell, Dragan A. Savic. 1465-1473 [doi]
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