Table of Contents

• AI for happiness of peopleKazuo Yano. 1 [doi]
• Exploitation of bio signal data to understand human stateTatsuya Okabe. 2 [doi]
• Connecting human and technologies in spaceNaoko Yamazaki. 3 [doi]
• On becoming a reflective practitionerDavid E. Goldberg. 4 [doi]
• Information sharing and conflict resolution in distributed factored evolutionary algorithmsStephyn G. W. Butcher, John W. Sheppard, Shane Strasser. 5-12 [doi]
• Using ant colony optimization to optimize long short-term memory recurrent neural networksAbdElRahman ElSaid, Fatima El Jamiy, James Higgins, Brandon Wild, Travis Desell. 13-20 [doi]
• A model of artificial emotions for behavior-modulation and implicit coordination in multi-robot systemsJérôme Guzzi, Alessandro Giusti, Luca Maria Gambardella, Gianni A. Di Caro. 21-28 [doi]
• Recurrent neural network-predictions for PSO in dynamic optimizationAlmuth Meier, Oliver Kramer. 29-36 [doi]
• A particle swarm optimization based feature selection approach to transfer learning in classificationBach Hoai Nguyen, Bing Xue, Peter Andreae. 37-44 [doi]
• Semi-supervised learning assisted particle swarm optimization of computationally expensive problemsChaoli Sun, Yaochu Jin, Ying Tan. 45-52 [doi]
• A new foraging-based algorithm for online schedulingKoen van der Blom, Thomas Bäck. 53-60 [doi]
• Towards the targeted environment-specific evolution of robot componentsJack Collins, Wade Geles, David Howard, Frédéric Maire. 61-68 [doi]
• Hierarchical behavioral repertoires with unsupervised descriptorsAntoine Cully, Yiannis Demiris. 69-76 [doi]
• How swarm size during evolution impacts the behavior, generalizability, and brain complexity of animats performing a spatial navigation taskDominik Fischer, Sanaz Mostaghim, Larissa Albantakis. 77-84 [doi]
• Data-efficient neuroevolution with kernel-based surrogate modelsAdam Gaier, Alexander Asteroth, Jean-Baptiste Mouret. 85-92 [doi]
• Fusing novelty and surprise for evolving robot morphologiesDaniele Gravina, Antonios Liapis, Georgios N. Yannakakis. 93-100 [doi]
• Evolution of a functionally diverse swarm via a novel decentralised quality-diversity algorithmEmma Hart, Andreas S. W. Steyven, Ben Paechter. 101-108 [doi]
• Interoceptive robustness through environment-mediated morphological developmentSam Kriegman, Nick Cheney, Francesco Corucci, Josh C. Bongard. 109-116 [doi]
• Safe mutations for deep and recurrent neural networks through output gradientsJoel Lehman, Jay Chen, Jeff Clune, Kenneth O. Stanley. 117-124 [doi]
• Real-world evolution adapts robot morphology and control to hardware limitationsTønnes F. Nygaard, Charles P. Martin, Eivind Samuelsen, Jim Tørresen, Kyrre Glette. 125-132 [doi]
• Automatic synthesis of swarm behavioural rules from their atomic componentsDilini Samarasinghe, Erandi Lakshika, Michael Barlow, Kathryn Kasmarik. 133-140 [doi]
• On an immuno-inspired distributed, embodied action-evolution cum selection algorithmTushar Semwal, Divya D. Kulkarni, Shivashankar B. Nair. 141-148 [doi]
• Discovering the elite hypervolume by leveraging interspecies correlationVassilis Vassiliades, Jean-Baptiste Mouret. 149-156 [doi]
• Evolution of fin undulation on a physical knifefish-inspired soft robotFrank Veenstra, Jonas Jørgensen, Sebastian Risi. 157-164 [doi]
• A robot to shape your natural plant: the machine learning approach to model and control bio-hybrid systemsMostafa Wahby, Mary Katherine Heinrich, Daniel Nicolas Hofstadler, Payam Zahadat, Sebastian Risi, Phil Ayres, Thomas Schmickl, Heiko Hamann. 165-172 [doi]
• Robotic snake simulation using ensembles of artificial neural networks in evolutionary roboticsGrant W. Woodford, Mathys C. du Plessis. 173-180 [doi]
• Generating beginner heuristics for simple texas hold'emFernando de Mesentier Silva, Julian Togelius, Frank Lantz, Andy Nealen. 181-188 [doi]
• Opponent modeling and exploitation in poker using evolved recurrent neural networksXun Li, Risto Miikkulainen. 189-196 [doi]
• Generating a melody based on symbiotic evolution for musicians' creative activitiesNoriko Otani, Daisuke Okabe, Masayuki Numao. 197-204 [doi]
• Evolving indirectly encoded convolutional neural networks to play tetris with low-level featuresJacob Schrum. 205-212 [doi]
• Querying across time to interactively evolve animationsIsabel Tweraser, Lauren E. Gillespie, Jacob Schrum. 213-220 [doi]
• Evolving mario levels in the latent space of a deep convolutional generative adversarial networkVanessa Volz, Jacob Schrum, Jialin Liu, Simon M. Lucas, Adam Smith, Sebastian Risi. 221-228 [doi]
• Evolving simple programs for playing atari gamesDennis G. Wilson, Sylvain Cussat-Blanc, Hervé Luga, Julian F. Miller. 229-236 [doi]
• Min-conflicts heuristic for multi-mode resource-constrained projects schedulingArben Ahmeti, Nysret Musliu. 237-244 [doi]
• An effective hybrid meta-heuristic for a heterogeneous flow shop scheduling problemMatheus de Freitas Araujo, José Elias C. Arroyo, Ricardo G. Tavares. 245-252 [doi]
• Algorithm selection on generalized quadratic assignment problem landscapesAndreas Beham, Stefan Wagner 0002, Michael Affenzeller. 253-260 [doi]
• A multi-objective formulation of the team formation problem in social networks: preliminary resultsJulio Juárez, Carlos A. Brizuela. 261-268 [doi]
• Enhancing partition crossover with articulation points analysisFrancisco Chicano, Gabriela Ochoa, Darrell Whitley, Renato Tinós. 269-276 [doi]
• A fitness landscape analysis of the travelling thief problemMohamed El Yafrani, Marcella S. R. Martins, Mehdi El Krari, Markus Wagner 0007, Myriam Regattieri de Biase da Silva Delgado, Belaïd Ahiod, Ricardo Lüders. 277-284 [doi]
• A heuristic algorithm based on tabu search for the solution of flexible job shop scheduling problems with lot streamingMiguel A. Fernández Romero, Eric Alfredo Rincón García, Antonin Ponsich, Román Mora Gutiérrez. 285-292 [doi]
• Escaping large deceptive basins of attraction with heavy-tailed mutation operatorsTobias Friedrich 0001, Francesco Quinzan, Markus Wagner 0007. 293-300 [doi]
• Improving the run time of the (1 + 1) evolutionary algorithm with luby sequencesTobias Friedrich 0001, Timo Kötzing, Francesco Quinzan, Andrew M. Sutton. 301-308 [doi]
• Randomized greedy algorithms for covering problemsWanru Gao, Tobias Friedrich 0001, Frank Neumann, Christian Hercher. 309-315 [doi]
• A merge search algorithm and its application to the constrained pit problem in miningAngus Kenny, Xiaodong Li 0001, Andreas T. Ernst. 316-323 [doi]
• Dominance, epsilon, and hypervolume local optimal sets in multi-objective optimization, and how to tell the differenceArnaud Liefooghe, Manuel López-Ibáñez 0001, Luís Paquete, Sébastien Vérel. 324-331 [doi]
• Evolutionary multi-level acyclic graph partitioningOrlando Moreira, Merten Popp, Christian Schulz 0003. 332-339 [doi]
• A two-level diploid genetic based algorithm for solving the family traveling salesman problemPetrica C. Pop, Oliviu Matei, Camelia-Mihaela Pintea. 340-346 [doi]
• Memetic multilevel hypergraph partitioningRobin Andre, Sebastian Schlag, Christian Schulz 0003. 347-354 [doi]
• Fitness landscape analysis around the optimum in computational protein designDavid Simoncini, Sophie Barbe, Thomas Schiex, Sébastien Vérel. 355-362 [doi]
• One-class constraint acquisition with local searchDaniel Sroka, Tomasz P. Pawlak. 363-370 [doi]
• Multifractality and dimensional determinism in local optima networksSarah L. Thomson, Sébastien Vérel, Gabriela Ochoa, Nadarajen Veerapen, David Cairns. 371-378 [doi]
• Iterated greedy algorithms for the hybrid flowshop scheduling with total flow time minimizationHande Öztop, Mehmet Fatih Tasgetiren, Deniz Türsel Eliiyi, Quan-ke Pan. 379-385 [doi]
• Combating catastrophic forgetting with developmental compressionShawn L. E. Beaulieu, Sam Kriegman, Josh C. Bongard. 386-393 [doi]
• Optimizing floating centroids method neural network classifier using dynamic multilayer particle swarm optimizationChangwei Cai, Shuangrong Liu, Lin Wang, Bo Yang, Zhenxiang Chen, Jin Zhou. 394-401 [doi]
• Autostacker: a compositional evolutionary learning systemBoyuan Chen, Harvey Wu, Warren Mo, Ishanu Chattopadhyay, Hod Lipson. 402-409 [doi]
• Neuroevolution of hierarchical reservoir computersMatthew Dale. 410-417 [doi]
• Evolving bagging ensembles using a spatially-structured niching methodGrant Dick, Caitlin A. Owen, Peter A. Whigham. 418-425 [doi]
• Online meta-learning by parallel algorithm competitionStefan Elfwing, Eiji Uchibe, Kenji Doya. 426-433 [doi]
• Evolved GANs for generating pareto set approximationsUnai Garciarena, Roberto Santana, Alexander Mendiburu. 434-441 [doi]
• Evolutionary expectation maximizationEnrico Guiraud, Jakob Drefs, Jörg Lücke. 442-449 [doi]
• ES is more than just a traditional finite-difference approximatorJoel Lehman, Jay Chen, Jeff Clune, Kenneth O. Stanley. 450-457 [doi]
• Automatically evolving difficult benchmark feature selection datasets with genetic programmingAndrew Lensen, Bing Xue, Mengjie Zhang. 458-465 [doi]
• Evolutionary architecture search for deep multitask networksJason Zhi Liang, Elliot Meyerson, Risto Miikkulainen. 466-473 [doi]
• Divide and conquer: neuroevolution for multiclass classificationTyler McDonnell, Sari Andoni, Elmira Bonab, Sheila Cheng, Jun-Hwan Choi, Jimmie Goode, Keith Moore, Gavin Sellers, Jacob Schrum. 474-481 [doi]
• Theoretical adaptation of multiple rule-generation in XCSMasaya Nakata, Will N. Browne, Tomoki Hamagami. 482-489 [doi]
• NEAT for large-scale reinforcement learning through evolutionary feature learning and policy gradient searchYiming Peng, Gang Chen 0002, Harman Singh, Mengjie Zhang. 490-497 [doi]
• A genetic algorithm for finding an optimal curing strategy for epidemic spreading in weighted networksClara Pizzuti, Annalisa Socievole. 498-504 [doi]
• Memetic evolution of deep neural networksPablo Ribalta Lorenzo, Jakub Nalepa. 505-512 [doi]
• Cooperative multi-objective evolutionary support vector machines for multiclass problemsAlejandro Rosales-Pérez, Andrés Eduardo Gutiérrez-Rodríguez, Salvador García, Hugo Terashima-Marín, Carlos A. Coello Coello, Francisco Herrera. 513-520 [doi]
• Towards an adaptive encoding for evolutionary data clusteringCameron Shand, Richard Allmendinger, Julia Handl, John Keane. 521-528 [doi]
• CovSel: A new approach for ensemble selection applied to symbolic regression problemsDominik Sobania, Franz Rothlauf. 529-536 [doi]
• What about interpolation?: a radial basis function approach to classifier prediction modeling in XCSFAnthony Stein, Simon Menssen, Jörg Hähner. 537-544 [doi]
• Efficient sample reuse in policy search by multiple importance samplingEiji Uchibe. 545-552 [doi]
• Attribute tracking: strategies towards improved detection and characterization of complex associationsRyan J. Urbanowicz, Christopher Lo, John H. Holmes, Jason H. Moore. 553-560 [doi]
• Ensembles of evolved nested dichotomies for classificationMarcel Wever, Felix Mohr, Eyke Hüllermeier. 561-568 [doi]
• Limited evaluation cooperative co-evolutionary differential evolution for large-scale neuroevolutionAnil Yaman, Decebal Constantin Mocanu, Giovanni Iacca, George H. L. Fletcher, Mykola Pechenizkiy. 569-576 [doi]
• Evolutionary feature subspaces generation for ensemble classificationBoyu Zhang, A. K. Qin, Timos Sellis. 577-584 [doi]
• Local search effects in bi-objective orienteeringJakob Bossek, Christian Grimme, Stephan Meisel, Günter Rudolph, Heike Trautmann. 585-592 [doi]
• Generalized offline orthant search: one code for many problems in multiobjective optimizationMaxim Buzdalov. 593-600 [doi]
• A differential prediction model for evolutionary dynamic multiobjective optimizationLeilei Cao, Lihong Xu, Erik D. Goodman, Shuwei Zhu, Hui Li 0020. 601-608 [doi]
• Surrogate-assisted evolutionary biobjective optimization for objectives with non-uniform latenciesTinkle Chugh, Richard Allmendinger, Vesa Ojalehto, Kaisa Miettinen. 609-616 [doi]
• A set-oriented MOEA/DBilel Derbel, Arnaud Liefooghe, Qingfu Zhang, Sébastien Vérel, Hernán E. Aguirre, Kiyoshi Tanaka. 617-624 [doi]
• Collaborative multi-objective optimization for distributed design of complex productsJoão A. Duro, Yiming Yan, Robin C. Purshouse, Peter J. Fleming. 625-632 [doi]
• A multi-objective evolutionary hyper-heuristic based on multiple indicator-based density estimatorsJesús Guillermo Falcón-Cardona, Carlos A. Coello Coello. 633-640 [doi]
• MOEA/D with uniformly randomly adaptive weightsLucas R. C. de Farias, Pedro H. M. Braga, Hansenclever de F. Bassani, Aluizio F. R. Araújo. 641-648 [doi]
• A taxonomy of methods for visualizing pareto front approximationsBogdan Filipic, Tea Tusar. 649-656 [doi]
• Data-driven analysis of pareto set topologyNaoki Hamada, Keisuke Goto. 657-664 [doi]
• Dual-grid model of MOEA/D for evolutionary constrained multiobjective optimizationHisao Ishibuchi, Takefumi Fukase, Naoki Masuyama, Yusuke Nojima. 665-672 [doi]
• Less detectable environmental changes in dynamic multiobjective optimisationShouyong Jiang, Marcus Kaiser, Jinglei Guo, Shengxiang Yang, Natalio Krasnogor. 673-680 [doi]
• Multiobjective sparse unmixing approach with noise removalXiangming Jiang, Maoguo Gong, Tao Zhan, Zedong Tang. 681-688 [doi]
• Component-level study of a decomposition-based multi-objective optimizer on a limited evaluation budgetOliver P. H. Jones, Jeremy E. Oakley, Robin C. Purshouse. 689-696 [doi]
• Efficient search techniques using adaptive discretization of design variables on real-coded evolutionary computationsToshiki Kondo, Tomoaki Tatsukawa. 697-704 [doi]
• Improving the performance of MO-RV-GOMEA on problems with many objectives using tchebycheff scalarizationsNgoc Hoang Luong, Tanja Alderliesten, Peter A. N. Bosnian. 705-712 [doi]
• +Edgar Manoatl Lopez, Carlos A. Coello Coello. 713-720 [doi]
• Directed mating in decomposition-based MOEA for constrained many-objective optimizationMinami Miyakawa, Hiroyuki Sato, Yuji Sato. 721-728 [doi]
• Transfer strategies from single- to multi-objective grouping mechanismsFrederick Sander, Heiner Zille, Sanaz Mostaghim. 729-736 [doi]
• mQAPViz: a divide-and-conquer multi-objective optimization algorithm to compute large data visualizationsClaudio Sanhueza, Francia Jiménez, Regina Berretta, Pablo Moscato. 737-744 [doi]
• A new R2 indicator for better hypervolume approximationKe Shang, Hisao Ishibuchi, Min-Ling Zhang, Yiping Liu. 745-752 [doi]
• Parallel pareto local search revisited: first experimental results on bi-objective UBQPJialong Shi, Qingfu Zhang, Bilel Derbel, Arnaud Liefooghe, Jianyong Sun. 753-760 [doi]
• Interactive multiobjective optimisation: preference changes and algorithm responsivenessKendall Taylor, Xiaodong Li. 761-768 [doi]
• Preference-based 3-dimensional en-route airspace sectorizationCheryl Sze Yin Wong, S. Suresh. 769-776 [doi]
• Evolutionary computation plus dynamic programming for the bi-objective travelling thief problemJunhua Wu, Sergey Polyakovskiy, Markus Wagner 0007, Frank Neumann. 777-784 [doi]
• A steady-state NSGA-II based multi-objective multicast routing algorithm for optical networksYing Xu, Yan Zhou. 785-792 [doi]
• Two enhancements for improving the convergence speed of a robust multi-objective coevolutionary algorithmAlexandru-Ciprian Zavoianu, Susanne Saminger-Platz, Edwin Lughofer, Wolfgang Amrhein. 793-800 [doi]
• Drift theory in continuous search spaces: expected hitting time of the (1 + 1)-ES with 1/5 success ruleYouhei Akimoto, Anne Auger, Tobias Glasmachers. 801-808 [doi]
• Analysis of evolution strategies with the optimal weighted recombinationChun-Kit Au, Ho-Fung Leung. 809-816 [doi]
• An empirical comparison of metamodeling strategies in noisy environmentsSunith Bandaru, Amos H. C. Ng. 817-824 [doi]
• Learning-based topology variation in evolutionary level set topology optimizationMariusz Bujny, Nikola Aulig, Markus Olhofer, Fabian Duddeck. 825-832 [doi]
• A global information based adaptive threshold for grouping large scale optimization problemsAn Chen, Yipeng Zhang, Zhigang Ren, Yang Yang, Yongsheng Liang, Bei Pang. 833-840 [doi]
• Inheritance-based diversity measures for explicit convergence control in evolutionary algorithmsThomas Gabor, Lenz Belzner, Claudia Linnhoff-Popien. 841-848 [doi]
• Expanding variational autoencoders for learning and exploiting latent representations in search distributionsUnai Garciarena, Roberto Santana, Alexander Mendiburu. 849-856 [doi]
• Real-valued evolutionary multi-modal optimization driven by hill-valley clusteringS. C. Maree, Tanja Alderliesten, Dirk Thierens, Peter A. N. Bosman. 857-864 [doi]
• PSA-CMA-ES: CMA-ES with population size adaptationKouhei Nishida, Youhei Akimoto. 865-872 [doi]
• Performance improvements for evolutionary strategy-based one-class constraint synthesisTomasz P. Pawlak. 873-880 [doi]
• A novel similarity-based mutant vector generation strategy for differential evolutionEduardo Segredo, Eduardo Lalla-Ruiz, Emma Hart. 881-888 [doi]
• Adaptive threshold parameter estimation with recursive differential grouping for problem decompositionYuan Sun 0003, Mohammad Nabi Omidvar, Michael Kirley, Xiaodong Li 0001. 889-896 [doi]
• Analysis of information geometric optimization with isotropic gaussian distribution under finite samplesKento Uchida, Shinichi Shirakawa, Youhei Akimoto. 897-904 [doi]
• Analysis of the use of genetic algorithms for indoor localisation via cloud point matchingMiguel d. Boland, Leandro Soares Indrusiak. 905-912 [doi]
• Fast algorithm for fair comparison of genetic algorithmsChia-Sheng Chen, Hung-Wei Hsu, Tian-Li Yu. 913-920 [doi]
• Tunneling between plateaus: improving on a state-of-the-art MAXSAT solver using partition crossoverWenxiang Chen, Darrell Whitley, Renato Tinós, Francisco Chicano. 921-928 [doi]
• Runtime analysis of probabilistic crowding and restricted tournament selection for bimodal optimisationEdgar Covantes Osuna, Dirk Sudholt. 929-936 [doi]
• Shaper-GA: automatic shape generation for modular house designBruno Taborda, Ana de Almeida, Filipe Santos, Sara Eloy, Krystian Kwiecinski. 937-942 [doi]
• Simple on-the-fly parameter selection mechanisms for two classical discrete black-box optimization benchmark problemsCarola Doerr, Markus Wagner 0007. 943-950 [doi]
• Towards a theory-guided benchmarking suite for discrete black-box optimization heuristics: profiling (1 + λ) EA variants on onemax and leadingonesCarola Doerr, Furong Ye, Sander van Rijn, Hao Wang 0025, Thomas Bäck. 951-958 [doi]
• Serendipitous scaffolding to improve a genetic algorithm's speed and qualityHeather J. Goldsby, Rebecca L. Young, Jory Schossau, Hans A. Hofmann, Arend Hintze. 959-966 [doi]
• On the runtime dynamics of the compact genetic algorithm on jump functionsVáclav Hasenöhrl, Andrew M. Sutton. 967-974 [doi]
• Investigation of the exponential population scheme for genetic algorithmsYuen-Jen Lin, Tian-Li Yu. 975-982 [doi]
• Learning an evolvable genotype-phenotype mappingMatthew Andres Moreno, Wolfgang Banzhaf, Charles Ofria. 983-990 [doi]
• Discrepancy-based evolutionary diversity optimizationAneta Neumann, Wanru Gao, Carola Doerr, Frank Neumann, Markus Wagner 0007. 991-998 [doi]
• GEESE: grammatical evolution algorithm for evolution of swarm behaviorsAadesh Neupane, Michael A. Goodrich, Eric G. Mercer. 999-1006 [doi]
• Learning bayesian network structures with GOMEAKalia Orphanou, Dirk Thierens, Peter A. N. Bosnian. 1007-1014 [doi]
• On the runtime analysis of selection hyper-heuristics with adaptive learning periodsBenjamin Doerr, Andrei Lissovoi, Pietro Simone Oliveto, John Alasdair Warwicker. 1015-1022 [doi]
• Sequential sampling for noisy optimisation with CMA-ESMatthew J. Groves, Jürgen Branke. 1023-1030 [doi]
• Adaptive asynchrony in semi-asynchronous evolutionary algorithm based on performance prediction using search historyTomohiro Harada. 1031-1038 [doi]
• Expected improvement of constraint violation for expensive constrained optimizationRuwang Jiao, Sanyou Zeng, Changhe Li, Yuhong Jiang, Junchen Wang. 1039-1046 [doi]
• Talakat: bullet hell generation through constrained map-elitesAhmed Khalifa, Scott Lee, Andy Nealen, Julian Togelius. 1047-1054 [doi]
• Neural estimation of interaction outcomesPawel Liskowski, Bartosz Wieloch, Krzysztof Krawiec. 1055-1062 [doi]
• Termination detection strategies in evolutionary algorithms: a surveyYanfeng Liu, Aimin Zhou, Hu Zhang 0002. 1063-1070 [doi]
• Memetic algorithms beat evolutionary algorithms on the class of hurdle problemsPhan Trung Hai Nguyen, Dirk Sudholt. 1071-1078 [doi]
• Cooperative co-evolution with online optimizer selection for large-scale optimizationYuan Sun 0003, Michael Kirley, Xiaodong Li. 1079-1086 [doi]
• Quasi-bistability of walk-based landscape measures in stochastic fitness landscapesBernhard Werth, Erik Pitzer, Gerald Ostermayer, Michael Affenzeller. 1087-1094 [doi]
• Changing or keeping solutions in dynamic optimization problems with switching costsDanial Yazdani, Jürgen Branke, Mohammad Nabi Omidvar, Trung Thanh Nguyen 0002, Xin Yao. 1095-1102 [doi]
• Working principles of binary differential evolutionWeijie Zheng, Guangwen Yang, Benjamin Doerr. 1103-1110 [doi]
• Schema-based diversification in genetic programmingBogdan Burlacu, Michael Affenzeller. 1111-1118 [doi]
• Towards effective semantic operators for program synthesis in genetic programmingStefan Forstenlechner, David Fagan, Miguel Nicolau, Michael O'Neill. 1119-1126 [doi]
• Program synthesis using uniform mutation by addition and deletionThomas Helmuth, Nicholas Freitag McPhee, Lee Spector. 1127-1134 [doi]
• Evolving event-driven programs with SignalGPAlexander Lalejini, Charles Ofria. 1135-1142 [doi]
• Neuro-guided genetic programming: prioritizing evolutionary search with neural networksPawel Liskowski, Iwo Bladek, Krzysztof Krawiec. 1143-1150 [doi]
• Solving the exponential growth of symbolic regression trees in geometric semantic genetic programmingJoao Francisco B. S. Martins, Luiz Otávio Vilas Boas Oliveira, Luis Fernando Miranda, Felipe Casadei, Gisele L. Pappa. 1151-1158 [doi]
• Adaptive charting genetic programming for dynamic flexible job shop schedulingSu Nguyen, Mengjie Zhang, Kay Chen Tan. 1159-1166 [doi]
• Genetic programming approach to learning multi-pass heuristics for resource constrained job schedulingSu Nguyen, Dhananjay R. Thiruvady, Andreas T. Ernst, Damminda Alahakoon. 1167-1174 [doi]
• Measuring evolvability and accessibility using the hyperlink-induced topic search algorithmKyle L. Nickerson, Yuanzhu Chen, Feng Wang, Ting Hu. 1175-1182 [doi]
• Where are we now?: a large benchmark study of recent symbolic regression methodsPatryk Orzechowski, William La Cava, Jason H. Moore. 1183-1190 [doi]
• An analysis of the bias of variation operators of estimation of distribution programmingDirk Schweim, Franz Rothlauf. 1191-1198 [doi]
• Large-scale parallelization of partial evaluations in evolutionary algorithms for real-world problemsAnton Bouter, Tanja Alderliesten, Arjan Bel, Cees Witteveen, Peter A. N. Bosman. 1199-1206 [doi]
• A rolling window with genetic algorithm approach to sorting aircraft for automated taxi routingAlexander E. I. Brownlee, John R. Woodward, Michal Weiszer, Jun Chen. 1207-1213 [doi]
• Genetic programming for tuberculosis screening from raw X-ray imagesArmand R. Burks, William F. Punch. 1214-1221 [doi]
• Value-based manufacturing optimisation in serverless clouds for industry 4.0Piotr Dziurzanski, Jerry Swan, Leandro Soares Indrusiak. 1222-1229 [doi]
• RateSetter: roadmap for faster, safer, and better platform train interface design and operation using evolutionary optimisationDavid Fletcher, Robert Harrison, Twin Karmakharm, Samadhi Nallaperuma, Paul Richmond. 1230-1237 [doi]
• Surrogate assisted optimization of particle reinforced metal matrix compositesLorenzo Gentile, Martin Zaefferer, Dario Giugliano, Haofeng Chen, Thomas Bartz-Beielstein. 1238-1245 [doi]
• Optimizing residential energy resources with an improved multi-objective genetic algorithm based on greedy mutationsIvo Gonçalves, Álvaro Gomes, Carlos Henggeler Antunes. 1246-1253 [doi]
• Investigation of the latent space of stock market patterns with genetic programmingSungjoo Ha, Sangyeop Lee, Byung Ro Moon. 1254-1261 [doi]
• Multi-objective journey planning under uncertainty: a genetic approachMohammad Haqqani, Xiaodong Li, Xinghuo Yu. 1262-1269 [doi]
• Genetic algorithm to study practical quantum adversariesWalter O. Krawec, Sam A. Markelon. 1270-1277 [doi]
• Predicting friction system performance with symbolic regression and genetic programming with factor variablesGabriel Kronberger, Michael Kommenda, Andreas Promberger, Falk Nickel. 1278-1285 [doi]
• Benchmarking evolutionary computation approaches to insider threat detectionDuc C. Le, Sara Khanchi, A. Nur Zincir-Heywood, Malcolm I. Heywood. 1286-1293 [doi]
• Informed mutation operator using machine learning for optimization in epidemics preventionKrzysztof Michalak. 1294-1301 [doi]
• Evolving boolean functions for fast and efficient randomness testingVojtech Mrazek, Marek Sýs, Zdenek Vasícek, Lukás Sekanina, Vashek Matyas. 1302-1309 [doi]
• Estimation of the heterogeneous strategies from action logKeiichi Namikoshi, Sachiyo Arai. 1310-1317 [doi]
• A detailed comparison of meta-heuristic methods for optimising wave energy converter placementsMehdi Neshat, Bradley Alexander, Markus Wagner 0007, Yuanzhong Xia. 1318-1325 [doi]
• Evolving the autosteering of a car featuring a realistically simulated steering responseVsevolod Nikulin, Albert Podusenko, Ivan Tanev, Katsunori Shimohara. 1326-1332 [doi]
• Multi-objective aerodynamic design with user preference using truncated expected hypervolume improvementPramudita Satria Palar, Kaifeng Yang, Koji Shimoyama, Michael Emmerich, Thomas Bäck. 1333-1340 [doi]
• Impacts of constraints and constraint handling strategies for multi-objective mechanical design problemsCyril Picard, Jürg Schiffmann. 1341-1347 [doi]
• Comparison of parallel surrogate-assisted optimization approachesFrederik Rehbach, Martin Zaefferer, Jörg Stork, Thomas Bartz-Beielstein. 1348-1355 [doi]
• Orthogonalization of linear representations for efficient evolutionary design optimizationAndreas Richter, Stefan Dresselhaus, Stefan Menzel, Mario Botsch. 1356-1363 [doi]
• A genetic programming based iterated local search for software project schedulingNasser R. Sabar, Ayad Turky, Andy Song. 1364-1370 [doi]
• A GA based network optimization tool for passive in-building distributed antenna systemsSiddhartha Shakya, Kin Fai Poon, Anis Ouali. 1371-1378 [doi]
• Functional generative design: an evolutionary approach to 3D-printingCem Celal Tutum, Supawit Chockchowwat, Etienne Vouga, Risto Miikkulainen. 1379-1386 [doi]
• Better and faster catheter position optimization in HDR brachytherapy for prostate cancer using multi-objective real-valued GOMEAMarjolein C. van der Meer, Bradley R. Pieters, Yury Niatsetski, Tanja Alderliesten, Arjan Bel, Peter A. N. Bosman. 1387-1394 [doi]
• Symbolic regression and feature construction with GP-GOMEA applied to radiotherapy dose reconstruction of childhood cancer survivorsMarco Virgolin, Tanja Alderliesten, Arjan Bel, Cees Witteveen, Peter A. N. Bosman. 1395-1402 [doi]
• Estimating cement compressive strength from microstructural images using GEP with probabilistic polarized similarity weight tournament selectionLiangLiang Zhang, Xinya Yue, Lin Wang, Bo Yang. 1403-1410 [doi]
• Multi-objective black-box test case selection for cost-effectively testing simulation modelsAitor Arrieta, Shuai Wang 0001, Ainhoa Arruabarrena, Urtzi Markiegi, Goiuria Sagardui, Leire Etxeberria. 1411-1418 [doi]
• On the effects of seeding strategies: a case for search-based multi-objective service compositionTao Chen 0001, Miqing Li, Xin Yao. 1419-1426 [doi]
• Test suite minimization for mutation testing of WS-BPEL compositionsFrancisco Palomo-Lozano, Antonia Estero-Botaro, Inmaculada Medina-Bulo, Manuel Núñez 0001. 1427-1434 [doi]
• Towards the automated recovery of complex temporal API-usage patternsMohamed Aymen Saied, Houari A. Sahraoui, Edouard Batot, Michalis Famelis, Pierre-Olivier Talbot. 1435-1442 [doi]
• A novel fitness function for automated program repair based on source code checkpointsEduardo Faria de Souza, Claire Le Goues, Celso Gonçalves Camilo-Junior. 1443-1450 [doi]
• Dependent input sampling strategies: using metaheuristics for generating parameterised random sampling regimesKomsan Srivisut, John A. Clark, Richard F. Paige. 1451-1458 [doi]
• A tight runtime analysis for the (μ + λ) EADenis Antipov, Benjamin Doerr, Jiefeng Fang, Tangi Hetet. 1459-1466 [doi]
• A new analysis method for evolutionary optimization of dynamic and noisy objective functionsRaphaël Dang-Nhu, Thibault Dardinier, Benjamin Doerr, Gautier Izacard, Dorian Nogneng. 1467-1474 [doi]
• Runtime analysis for self-adaptive mutation ratesBenjamin Doerr, Carsten Witt, Jing Yang 0016. 1475-1482 [doi]
• Significance-based estimation-of-distribution algorithmsBenjamin Doerr, Martin S. Krejca. 1483-1490 [doi]
• The linear hidden subset problem for the (1 + 1) EA with scheduled and adaptive mutation ratesHafsteinn Einarsson, Johannes Lengler, Marcelo Matheus Gauy, Florian Meier, Asier Mujika, Angelika Steger, Felix Weissenberger. 1491-1498 [doi]
• Medium step sizes are harmful for the compact genetic algorithmJohannes Lengler, Dirk Sudholt, Carsten Witt. 1499-1506 [doi]
• Analysis of noisy evolutionary optimization when sampling failsChao Qian, Chao Bian, Yang Yu 0001, Ke Tang, Xin Yao. 1507-1514 [doi]
• Runtime analysis of randomized search heuristics for the dynamic weighted vertex cover problemFeng Shi, Frank Neumann, Jianxin Wang. 1515-1522 [doi]
• On the robustness of evolutionary algorithms to noise: refined results and an example where noise helpsDirk Sudholt. 1523-1530 [doi]
• Crossover can simulate bounded tree search on a fixed-parameter tractable optimization problemAndrew M. Sutton. 1531-1538 [doi]
• Domino convergence: why one should hill-climb on linear functionsCarsten Witt. 1539-1546 [doi]