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Pablo Moscato
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2020 – today
- 2024
- [j35]Brendan Rogers, Nasimul Noman, Stephan K. Chalup, Pablo Moscato:
A comparative analysis of deep neural network architectures for sentence classification using genetic algorithm. Evol. Intell. 17(3): 1933-1952 (2024) - [c48]Guillaume Briffoteaux, Andrew Ciezak, Pablo Moscato:
Towards Target Derivatives-Enhanced Continued Fraction Regression. GECCO Companion 2024: 81-82 - [i8]Sarwan Ali, Pablo Moscato:
A Memetic Algorithm To Find a Hamiltonian Cycle in a Hamiltonian Graph. CoRR abs/2403.07886 (2024) - 2023
- [j34]Pablo Moscato, Mohammad Nazmul Haque, Kevin Huang, Julia Sloan, Jon Corrales de Oliveira:
Learning to Extrapolate Using Continued Fractions: Predicting the Critical Temperature of Superconductor Materials. Algorithms 16(8): 382 (2023) - [j33]Bo Zhang, Hongyu Zhang, Van-Hoang Le, Pablo Moscato, Aozhong Zhang:
Semi-supervised and unsupervised anomaly detection by mining numerical workflow relations from system logs. Autom. Softw. Eng. 30(1): 4 (2023) - [c47]Pablo Moscato, Andrew Ciezak, Nasimul Noman:
Dynamic Depth for Better Generalization in Continued Fraction Regression. GECCO 2023: 520-528 - [c46]Pablo Moscato, Rafael Bartnik Grebogi:
Approximating the Boundaries of Unstable Nuclei Using Analytic Continued Fractions. GECCO Companion 2023: 751-754 - 2022
- [j32]Pablo Moscato, Hugh Craig, Gabriel Egan, Mohammad Nazmul Haque, Kevin Huang, Julia Sloan, Jon Corrales de Oliveira:
Multiple regression techniques for modelling dates of first performances of Shakespeare-era plays. Expert Syst. Appl. 200: 116903 (2022) - [j31]Eneko Osaba, Javier Del Ser, Carlos Cotta, Pablo Moscato:
Editorial: Memetic Computing: Accelerating optimization heuristics with problem-dependent local search methods. Swarm Evol. Comput. 70: 101047 (2022) - [c45]Brendan Rogers, Nasimul Noman, Stephan K. Chalup, Pablo Moscato:
Joint Optimization of Topology and Hyperparameters of Hybrid DNNs for Sentence Classification. CEC 2022: 1-8 - 2021
- [j30]Pablo Moscato, Haoyuan Sun, Mohammad Nazmul Haque:
Analytic Continued Fractions for Regression: A Memetic Algorithm Approach. Expert Syst. Appl. 179: 115018 (2021) - [j29]Pablo Moscato, Luke Mathieson, Mohammad Nazmul Haque:
Augmented intuition: a bridge between theory and practice. J. Heuristics 27(4): 497-547 (2021) - [c44]Brendan Rogers, Nasimul Noman, Stephan K. Chalup, Pablo Moscato:
Evolutionary Hyperparameter Optimisation for Sentence Classification. CEC 2021: 958-965 - [i7]Pablo Moscato, Hugh Craig, Gabriel Egan, Mohammad Nazmul Haque, Kevin Huang, Julia Sloan, Jon Corrales de Oliveira:
Multiple regression techniques for modeling dates of first performances of Shakespeare-era plays. CoRR abs/2104.05929 (2021) - 2020
- [j28]Ademir C. Gabardo, Regina Berretta, Pablo Moscato:
M-Link: a link clustering memetic algorithm for overlapping community detection. Memetic Comput. 12(2): 87-99 (2020) - [j27]Nasimul Noman, Pablo Moscato:
Designing optimal combination therapy for personalised glioma treatment. Memetic Comput. 12(4): 317-329 (2020) - [c43]Pablo Moscato, Haoyuan Sun, Mohammad Nazmul Haque:
Analytic Continued Fractions for Regression: Results on 352 datasets from the physical sciences. CEC 2020: 1-8 - [c42]Bo Zhang, Hongyu Zhang, Pablo Moscato, Aozhong Zhang:
Anomaly Detection via Mining Numerical Workflow Relations from Logs. SRDS 2020: 195-204 - [c41]Luke Mathieson, Pablo Moscato:
The Unexpected Virtue of Problem Reductions or How to Solve Problems Being Lazy but Wise. SSCI 2020: 2381-2390 - [i6]Pablo Moscato, Haoyuan Sun, Mohammad Nazmul Haque:
Analytic Continued Fractions for Regression: A Memetic Algorithm Approach. CoRR abs/2001.00624 (2020) - [i5]Pablo Moscato, Mohammad Nazmul Haque, Kevin Huang, Julia Sloan, Jon Corrales de Oliveira:
Learning to extrapolate using continued fractions: Predicting the critical temperature of superconductor materials. CoRR abs/2012.03774 (2020)
2010 – 2019
- 2019
- [j26]Amer Abu Zaher, Regina Berretta, Nasimul Noman, Pablo Moscato:
An adaptive memetic algorithm for feature selection using proximity graphs. Comput. Intell. 35(1): 156-183 (2019) - [j25]Mohammad Nazmul Haque, Pablo Moscato:
The Cohesion-Based Communities of Symptoms of the Largest Component of the DSM-IV Network. J. Interconnect. Networks 19(1): 1940002:1-1940002:20 (2019) - [c40]Terry Truong, Pablo Moscato, Nasimul Noman:
A Computational Approach for Designing Combination Therapy in Combating Glioblastoma. CEC 2019: 127-134 - [c39]Haoyuan Sun, Pablo Moscato:
A Memetic Algorithm for Symbolic Regression. CEC 2019: 2167-2174 - [c38]Mohammad Nazmul Haque, Luke Mathieson, Pablo Moscato:
A memetic algorithm approach to network alignment: mapping the classification of mental disorders of DSM-IV with ICD-10. GECCO 2019: 258-265 - [c37]Bo Zhang, Hongyu Zhang, Junjie Chen, Dan Hao, Pablo Moscato:
Automatic Discovery and Cleansing of Numerical Metamorphic Relations. ICSME 2019: 235-245 - [c36]Bo Zhang, Hongyu Zhang, Junjie Chen, Dan Hao, Pablo Moscato:
AutoMR: Automatic Discovery and Cleansing of Numerical Metamorphic Relations. ICSME 2019: 246 - [p17]Pablo Moscato, Natalie Jane de Vries:
Marketing Meets Data Science: Bridging the Gap. Business and Consumer Analytics: New Ideas 2019: 3-117 - [p16]Natalie Jane de Vries, Pablo Moscato:
Consumer Behaviour and Marketing Fundamentals for Business Data Analytics. Business and Consumer Analytics: New Ideas 2019: 119-162 - [p15]Natalie Jane de Vries, Lukasz P. Olech, Pablo Moscato:
Introducing Clustering with a Focus in Marketing and Consumer Analysis. Business and Consumer Analytics: New Ideas 2019: 165-212 - [p14]Luke Mathieson, Pablo Moscato:
An Introduction to Proximity Graphs. Business and Consumer Analytics: New Ideas 2019: 213-233 - [p13]Natalie Jane de Vries, Jamie Carlson, Pablo Moscato:
Clustering Consumers and Cluster-Specific Behavioural Models. Business and Consumer Analytics: New Ideas 2019: 235-267 - [p12]Pablo Moscato:
Business Network Analytics: From Graphs to Supernetworks. Business and Consumer Analytics: New Ideas 2019: 307-400 - [p11]Ademir C. Gabardo, Regina Berretta, Pablo Moscato:
Overlapping Communities in Co-purchasing and Social Interaction Graphs: A Memetic Approach. Business and Consumer Analytics: New Ideas 2019: 435-466 - [p10]Luke Mathieson, Natalie Jane de Vries, Pablo Moscato:
Using Network Alignment to Identify Conserved Consumer Behaviour Modelling Constructs. Business and Consumer Analytics: New Ideas 2019: 513-541 - [p9]Pablo Moscato, Luke Mathieson:
Memetic Algorithms for Business Analytics and Data Science: A Brief Survey. Business and Consumer Analytics: New Ideas 2019: 545-608 - [p8]Claudio Sanhueza Lobos, Natalie Jane de Vries, Mario Inostroza-Ponta, Regina Berretta, Pablo Moscato:
Visualizing Products and Consumers: A Gestalt Theory Inspired Method. Business and Consumer Analytics: New Ideas 2019: 661-689 - [p7]Mohammad Nazmul Haque, Pablo Moscato:
From Ensemble Learning to Meta-Analytics: A Review on Trends in Business Applications. Business and Consumer Analytics: New Ideas 2019: 703-731 - [p6]Mohammad Nazmul Haque, Natalie Jane de Vries, Pablo Moscato:
A Multi-objective Meta-Analytic Method for Customer Churn Prediction. Business and Consumer Analytics: New Ideas 2019: 781-813 - [p5]Natalie Jane de Vries, Pablo Moscato:
Datasets for Business and Consumer Analytics. Business and Consumer Analytics: New Ideas 2019: 965-987 - [e2]Pablo Moscato, Natalie Jane de Vries:
Business and Consumer Analytics: New Ideas. Springer 2019, ISBN 978-3-030-06221-7 [contents] - 2018
- [j24]Nader Mahmoudi, Paul Docherty, Pablo Moscato:
Deep neural networks understand investors better. Decis. Support Syst. 112: 23-34 (2018) - [c35]Jake Fitzsimmons, Pablo Moscato:
Symbolic Regression Modeling of Drug Responses. AI4I 2018: 52-59 - [c34]Francia Jiménez, Claudio Sanhueza, Regina Berretta, Pablo Moscato:
Accelerating a multi-objective memetic algorithm for feature selection using hierarchical k-means indexes. GECCO (Companion) 2018: 181-182 - [c33]Claudio Sanhueza, Francia Jiménez, Regina Berretta, Pablo Moscato:
mQAPViz: a divide-and-conquer multi-objective optimization algorithm to compute large data visualizations. GECCO 2018: 737-744 - [r4]Carlos Cotta, Luke Mathieson, Pablo Moscato:
Memetic Algorithms. Handbook of Heuristics 2018: 607-638 - [r3]Mario Inostroza-Ponta, Natalie Jane de Vries, Pablo Moscato:
World's Best Universities and Personalized Rankings. Handbook of Heuristics 2018: 1335-1371 - [i4]Claudio Sanhueza, Francia Jiménez, Regina Berretta, Pablo Moscato:
mQAPViz: A divide-and-conquer multi-objective optimization algorithm to compute large data visualizations. CoRR abs/1804.00656 (2018) - 2017
- [j23]Shannon Fenn, Pablo Moscato:
Target Curricula via Selection of Minimum Feature Sets: a Case Study in Boolean Networks. J. Mach. Learn. Res. 18: 114:1-114:26 (2017) - [j22]Giuseppe Lancia, Luke Mathieson, Pablo Moscato:
Separating sets of strings by finding matching patterns is almost always hard. Theor. Comput. Sci. 665: 73-86 (2017) - [c32]Claudio Sanhueza, Francia Jimenez, Regina Berretta, Pablo Moscato:
PasMoQAP: A parallel asynchronous memetic algorithm for solving the Multi-Objective Quadratic Assignment Problem. CEC 2017: 1103-1110 - [c31]Francia Jimenez, Claudio Sanhueza, Regina Berretta, Pablo Moscato:
A multi-objective approach for the (α, β)-k-feature set problem using memetic algorithms. GECCO (Companion) 2017: 207-208 - [c30]Mohammad Nazmul Haque, Luke Mathieson, Pablo Moscato:
A memetic algorithm for community detection by maximising the connected cohesion. SSCI 2017: 1-8 - [i3]Shannon Fenn, Pablo Moscato:
Target Curricula via Selection of Minimum Feature Sets: a Case Study in Boolean Networks. CoRR abs/1706.04721 (2017) - [i2]Claudio Sanhueza, Francia Jimenez, Regina Berretta, Pablo Moscato:
PasMoQAP: A Parallel Asynchronous Memetic Algorithm for solving the Multi-Objective Quadratic Assignment Problem. CoRR abs/1706.08700 (2017) - 2016
- [j21]Heloisa H. Milioli, Renato Vimieiro, Inna Tishchenko, Carlos Riveros, Regina Berretta, Pablo Moscato:
Iteratively refining breast cancer intrinsic subtypes in the METABRIC dataset. BioData Min. 9: 2 (2016) - [j20]José A. Lachiondo, Manuel Ujaldon, Regina Berretta, Pablo Moscato:
Legendre moments as high performance bone biomarkers: computational methods and GPU acceleration. Comput. methods Biomech. Biomed. Eng. Imaging Vis. 4(3-4): 146-163 (2016) - [j19]Luiz Fernando Nunes, Lauro Cesar Galvão, Heitor Silvério Lopes, Pablo Moscato, Regina Berretta:
An integer programming model for protein structure prediction using the 3D-HP side chain model. Discret. Appl. Math. 198: 206-214 (2016) - [j18]Mateus Rocha de Paula, Regina Berretta, Pablo Moscato:
A fast meta-heuristic approach for the (α, β)-k-feature set problem. J. Heuristics 22(2): 199-220 (2016) - [c29]Natalie Jane de Vries, Ahmed Shamsul Arefin, Luke Mathieson, Benjamin Lucas, Pablo Moscato:
Relative Neighborhood Graphs Uncover the Dynamics of Social Media Engagement. ADMA 2016: 283-297 - [c28]Mohammad Nazmul Haque, Nasimul Noman, Regina Berretta, Pablo Moscato:
Optimising weights for heterogeneous ensemble of classifiers with differential evolution. CEC 2016: 233-240 - [c27]Ademir C. Gabardo, Regina Berretta, Natalie Jane de Vries, Pablo Moscato:
Proceedings in Adaptation, Learning and Optimization. IES 2016: 133-148 - [i1]Giuseppe Lancia, Luke Mathieson, Pablo Moscato:
Finding Patterns is Almost Always Hard. CoRR abs/1604.03243 (2016) - 2015
- [c26]Ahmed Shamsul Arefin, Carlos Riveros, Regina Berretta, Pablo Moscato:
The MST-kNN with Paracliques. ACALCI 2015: 373-386 - [c25]Ahmed Shamsul Arefin, Regina Berretta, Pablo Moscato:
On Ranking Nodes using kNN Graphs, Shortest-paths and GPUs. AusDM 2015: 29-38 - [c24]Amer Abu Zaher, Regina Berretta, Ahmed Shamsul Arefin, Pablo Moscato:
FSMEC: A Feature Selection Method based on the Minimum Spanning Tree and Evolutionary Computation. AusDM 2015: 129-139 - [c23]Matthew Harris, Regina Berretta, Mario Inostroza-Ponta, Pablo Moscato:
A Memetic Algorithm for the Quadratic Assignment Problem with parallel local search. CEC 2015: 838-845 - 2014
- [j17]Renato Vimieiro, Pablo Moscato:
A new method for mining disjunctive emerging patterns in high-dimensional datasets using hypergraphs. Inf. Syst. 40: 1-10 (2014) - [j16]Renato Vimieiro, Pablo Moscato:
Disclosed: An efficient depth-first, top-down algorithm for mining disjunctive closed itemsets in high-dimensional data. Inf. Sci. 280: 171-187 (2014) - [j15]Manuel Jesús Martín-Requena, Pablo Moscato, Manuel Ujaldon:
Efficient data partitioning for the GPU computation of moment functions. J. Parallel Distributed Comput. 74(1): 1994-2004 (2014) - [c22]Benjamin Lucas, Ahmed Shamsul Arefin, Natalie Jane de Vries, Regina Berretta, Jamie Carlson, Pablo Moscato:
Engagement in Motion: Exploring Short Term Dynamics in Page-Level Social Media Metrics. BDCloud 2014: 334-341 - [c21]Natalie Jane de Vries, Ahmed Shamsul Arefin, Pablo Moscato:
Gauging Heterogeneity in Online Consumer Behaviour Data: A Proximity Graph Approach. BDCloud 2014: 485-492 - [c20]Leila Moslemi Naeni, Natalie Jane de Vries, Rodrigo Reis, Ahmed Shamsul Arefin, Regina Berretta, Pablo Moscato:
Identifying Communities of Trust and Confidence in the Charity and Not-for-Profit Sector: A Memetic Algorithm Approach. BDCloud 2014: 500-507 - [c19]Carlos Riveros, Manuel Ujaldon, Pablo Moscato:
Entropy-based High Performance Computation of Boolean SNP-SNP Interactions Using GPUs. IWBBIO 2014: 539-550 - 2012
- [j14]Renato Vimieiro, Pablo Moscato:
Mining disjunctive minimal generators with TitanicOR. Expert Syst. Appl. 39(9): 8228-8238 (2012) - [c18]Lauro Cesar Galvão, Luiz Fernando Nunes, Heitor Silvério Lopes, Pablo Moscato:
A new greedy heuristic for 3DHP protein struture prediction with side chain. BIBM Workshops 2012: 77-81 - [c17]Ahmed Shamsul Arefin, Carlos Riveros, Regina Berretta, Pablo Moscato:
kNN-Borůvka-GPU: A Fast and Scalable MST Construction from kNN Graphs on GPU. ICCSA (1) 2012: 71-86 - [p4]Regina Berretta, Carlos Cotta, Pablo Moscato:
Memetic Algorithms in Bioinformatics. Handbook of Memetic Algorithms 2012: 261-271 - [p3]Pablo Moscato:
Memetic Algorithms: The Untold Story. Handbook of Memetic Algorithms 2012: 275-309 - [e1]Ferrante Neri, Carlos Cotta, Pablo Moscato:
Handbook of Memetic Algorithms. Studies in Computational Intelligence 379, Springer 2012, ISBN 978-3-642-23246-6 [contents] - 2011
- [c16]Farhan Ahammed, Pablo Moscato:
Evolving L-Systems as an Intelligent Design Approach to Find Classes of Difficult-to-Solve Traveling Salesman Problem Instances. EvoApplications (1) 2011: 1-11 - [c15]Ahmed Shamsul Arefin, Mario Inostroza-Ponta, Luke Mathieson, Regina Berretta, Pablo Moscato:
Clustering Nodes in Large-Scale Biological Networks Using External Memory Algorithms. ICA3PP (2) 2011: 375-386 - 2010
- [j13]Aaron Ikin, Carlos Riveros, Pablo Moscato, Alexandre Mendes:
The Gene Interaction Miner: a new tool for data mining contextual information for protein-protein interaction analysis. Bioinform. 26(2): 283-284 (2010) - [j12]Gary L. Rogers, Pablo Moscato, Michael A. Langston:
Graph algorithms for machine learning: a case-control study based on prostate cancer populations and high throughput transcriptomic data. BMC Bioinform. 11(S-4): P21 (2010)
2000 – 2009
- 2009
- [p2]Martín Gómez Ravetti, Regina Berretta, Pablo Moscato:
Novel Biomarkers for Prostate Cancer Revealed by (α, β)-k-Feature Sets. Foundations of Computational Intelligence (5) 2009: 149-175 - 2008
- [c14]Luciana Montera, Maria do Carmo Nicoletti, Flavio Henrique da Silva, Pablo Moscato:
An effective mutation-based measure for evaluating the suitability of parental sequences to undergo DNA shuffling experiments. IEEE Congress on Evolutionary Computation 2008: 765-772 - 2007
- [j11]Regina Berretta, Alexandre Mendes, Pablo Moscato:
Selection of Discriminative Genes in Microarray Experiments Using Mathematical Programming. J. Res. Pract. Inf. Technol. 39(4): 287-299 (2007) - [j10]Pablo Moscato, Alexandre Mendes, Regina Berretta:
Benchmarking a memetic algorithm for ordering microarray data. Biosyst. 88(1-2): 56-75 (2007) - [c13]Mario Inostroza-Ponta, Alexandre Mendes, Regina Berretta, Pablo Moscato:
An Integrated QAP-Based Approach to Visualize Patterns of Gene Expression Similarity. ACAL 2007: 156-167 - [r2]Carlos Cotta, Pablo Moscato:
Memetic Algorithms. Handbook of Approximation Algorithms and Metaheuristics 2007 - [r1]Michael A. Langston, Carlos Cotta, Pablo Moscato:
Combinatorial and Algorithmic Issues for Microarray Analysis. Handbook of Approximation Algorithms and Metaheuristics 2007 - 2006
- [c12]Pritha Mahata, Wagner Costa, Carlos Cotta, Pablo Moscato:
Hierarchical Clustering, Languages and Cancer. EvoWorkshops 2006: 67-78 - [c11]Mario Inostroza-Ponta, Regina Berretta, Alexandre Mendes, Pablo Moscato:
An automatic graph layout procedure to visualize correlated data. IFIP AI 2006: 179-188 - [c10]Vinícius Garcia, Paulo Morelato França, Alexandre Mendes, Pablo Moscato:
A parallel memetic algorithm applied to the total tardiness machine scheduling problem. IPDPS 2006 - 2005
- [j9]Paulo Morelato França, Jatinder N. D. Gupta, Alexandre Mendes, Pablo Moscato, Klaas J. Veltink:
Evolutionary algorithms for scheduling a flowshop manufacturing cell with sequence dependent family setups. Comput. Ind. Eng. 48(3): 491-506 (2005) - [c9]Regina Berretta, Alexandre Mendes, Pablo Moscato:
Integer Programming Models and Algorithms for Molecular Classification of Cancer from Microarray Data. ACSC 2005: 361-370 - [c8]Pablo Moscato, Luke Mathieson, Alexandre Mendes, Regina Berretta:
The Electronic Primaries: Predicting the U.S. Presidency Using Feature Selection with Safe Data Reduction. ACSC 2005: 371-380 - [c7]Pablo Moscato, Regina Berretta, Mou'ath Hourani, Alexandre Mendes, Carlos Cotta:
Genes Related with Alzheimer's Disease: A Comparison of Evolutionary Search, Statistical and Integer Programming Approaches. EvoWorkshops 2005: 84-94 - [c6]Alexandre Mendes, Carlos Cotta, Vinícius Garcia, Paulo Morelato França, Pablo Moscato:
Gene Ordering in Microarray Data Using Parallel Memetic Algorithms. ICPP Workshops 2005: 604-611 - 2004
- [j8]Lalinka de Campos Teixeira Gomes, Fernando J. Von Zuben, Pablo Moscato:
A proposal for direct-ordering gene expression data by self-organising maps. Appl. Soft Comput. 5(1): 11-21 (2004) - [j7]Luciana S. Buriol, Paulo Morelato França, Pablo Moscato:
A New Memetic Algorithm for the Asymmetric Traveling Salesman Problem. J. Heuristics 10(5): 483-506 (2004) - [c5]Carlos Cotta, Christian Sloper, Pablo Moscato:
Evolutionary Search of Thresholds for Robust Feature Set Selection: Application to the Analysis of Microarray Data. EvoWorkshops 2004: 21-30 - 2003
- [j6]Pablo Moscato, Carlos Cotta:
Una Introducción a los Algoritmos Memeticos. Inteligencia Artif. 7(19): 131-148 (2003) - [j5]Carlos Cotta, Pablo Moscato:
A mixed evolutionary-statistical analysis of an algorithm's complexity. Appl. Math. Lett. 16(1): 41-47 (2003) - [j4]Carlos Cotta, Pablo Moscato:
The k-FEATURE SET problem is W[2]-complete. J. Comput. Syst. Sci. 67(4): 686-690 (2003) - [c4]Carlos Cotta, Alexandre Mendes, Vinícius Garcia, Paulo Morelato França, Pablo Moscato:
Applying Memetic Algorithms to the Analysis of Microarray Data. EvoWorkshops 2003: 22-32 - [p1]Pablo Moscato, Carlos Cotta:
A Gentle Introduction to Memetic Algorithms. Handbook of Metaheuristics 2003: 105-144 - 2002
- [c3]Alexandre Mendes, Paulo Morelato França, Pablo Moscato, Vinícius Garcia:
Population Studies for the Gate Matrix Layout Problem. IBERAMIA 2002: 319-339 - [c2]Carlos Cotta, Pablo Moscato:
Inferring Phylogenetic Trees Using Evolutionary Algorithms. PPSN 2002: 720-729 - [c1]Lalinka de C. T. Gomes, Fernando J. Von Zuben, Pablo Moscato:
Ordering Gene Expression Data Using One-dimensional Self-Organizing Maps. WOB 2002: 91-93 - 2001
- [j3]Paulo Morelato França, Alexandre Mendes, Pablo Moscato:
A memetic algorithm for the total tardiness single machine scheduling problem. Eur. J. Oper. Res. 132(1): 224-242 (2001)
1990 – 1999
- 1998
- [j2]Pablo Moscato, Michael G. Norman:
On the Performance of Heuristics on Finite and Infinite Fractal Instances of the Euclidean Traveling Salesman Problem. INFORMS J. Comput. 10(2): 121-132 (1998) - 1993
- [j1]