Most cited publications

My h-index is 40. The following are my forty most cited publications (see Google Scholar for an up to date version of this list)


[J12] M. Dorigo, M. Birattari, and T. Stützle (2006). Ant colony optimization: Artificial ants as a computational intelligence technique. [PDF] IEEE Computational Intelligence Magazine, 1(4):28-39 [9722 citations]

[P18] M. Birattari, T. Stützle, L. Paquete, and K. Varrentrapp (2002). A racing algorithm for configuring metaheuristics. [PDF] In W.B. Langdon, E. Cantú-Paz, K. Mathias, R. Roy, D. Davis, R. Poli, K. Balakrishnan, V. Honavar, G. Rudolph, J. Wegener, L. Bull, M.A. Potter, A.C. Schultz, J.F. Miller, E. Burke, and N. Jonoska (Eds.) GECCO 2002: Proceedings of the Genetic and Evolutionary Computation Conference, pp. 11-18. Morgan Kaufmann, San Francisco, CA, USA [515 citations] — Winner of the 2012 SIGEVO Impact Award

[J33] M. Brambilla, E. Ferrante, M. Birattari, and M. Dorigo (2013).   Swarm robotics: A review from the swarm engineering perspective.[PDF]   Swarm Intelligence, 7(1):1-41 [378 citations]

[R095] M. López-Ibáñez, J. Dubois-Lacoste, T. Stützle, and M. Birattari (2011).   The irace package — Iterated race for automatic algorithm configuration.  Technical Report TR/IRIDIA/2011-004.   IRIDIA, Université Libre de Bruxelles, Brussels, Belgium [291 citations]

[J05] M. Zlochin, M. Birattari, N. Meuleau, and M. Dorigo (2004). Model-based search for combinatorial optimization: A critical survey. [PDF] Annals of Operations Research, 131: 373-395 [263 citations]

[J01] G. Bontempi, M. Birattari, and H. Bersini (1999). Lazy learning for local modeling and control design. [PDF] International Journal of Control, 72(7/8):643-658 [255 citations]

[J20] M. A. Montes de Oca, T. Stützle, M. Birattari, and M. Dorigo (2009).   Frankenstein's PSO: A composite particle swarm optimization algorithm. [PDF]   IEEE Transactions on Evolutionary Computation, 13(5):1120-1132 [253 citations]

[J15] M. Dorigo and M. Birattari (2007).   Swarm Intelligence. [PDF]   Scholarpedia, 2(9):1462 [242 citations]

[B02] M. Birattari (2009). Tuning Metaheuristics: A machine learning perspective. Springer, Berlin, Germany [237 citations]

[C05] M. Birattari, Z. Yuan, P. Balaprakash, and T. Stützle (2010).   F-race and iterated F-race: An overview.   In T. Bartz-Beielstein, M. Chiarandini, L. Paquete, and M. Preuss (Eds.) Empirical Methods for the Analysis of Optimization Algorithms, pp. 311-336, Springer, Berlin, Germany [220 citations]

[J38] M. Dorigo, D. Floreano, L. M. Gambardella, F. Mondada, S. Nolfi, T. Baaboura, M. Birattari, M. Bonani, M. Brambilla, A. Brutschy, D. Burnier, A. Campo, A. L. Christensen, A. Decugnière, G. Di Caro, F. Ducatelle, E. Ferrante, A. Förster, J. Martinez Gonzales, J. Guzzi, V. Longchamp, S. Magnenat, N. Mathews, M. Montes de Oca, R. O'Grady, C. Pinciroli, G. Pini, P. Rètornaz, J. Roberts, V. Sperati, T. Stirling, A. Stranieri, T. Stützle, V. Trianni, E. Tuci, A. E. Turgut, and F. Vaussard (2013).   Swarmanoid: A novel concept for the study of heterogeneous robotic swarms.   IEEE Robotics & Automation Magazine. 20(4)60-71 [204 citations]

[C02] O. Rossi-Doria, M. Sampels, M. Birattari, M. Chiarandini, M. Dorigo, L.M. Gambardella, J. Knowles, M. Manfrin, M. Mastrolilli, B. Paechter, L. Paquete, and T. Stützle (2003). A comparison of the performance of different metaheuristics on the timetabling problem. [PDF] In E. Burke and P.D Causmaecker (Eds.) Practice and Theory of Automated Timetabling IV. 4th International Conference, PATAT 2002. LNCS 2740, pp. 329-351. Springer, Berlin, Germany [202 citations]

[P37] P. Balaprakash, M. Birattari, T. Stützle (2007).   Improvement strategies for the F-Race algorithm: Sampling design and iterative refinement. [PDF]   In T. Bartz-Beielstein, M. J. Blesa Aguilera, C. Blum, B. Naujoks, A. Roli, G. Rudolph, and M. Sampels (Eds.) Hybrid Metaheuristics, 4th International Workshop, HM 2007, LNCS 4771, pp. 108-122. Springer. Berlin, Germany [188 citations]

[T03] M. Birattari (2004).   The Problem of Tuning Metaheuristics as Seen from a Machine Learning Perspective. [PDF]   PhD Thesis, Université Libre de Bruxelles. [175 citations]

[J10] M. Chiarandini, M. Birattari, K. Socha, and O. Rossi-Doria (2006). An effective hybrid algorithm for university course timetabling. [PDF] Journal of Scheduling, 9(5):403-432 [173 citations]

[J09] L. Bianchi, M. Birattari, M. Chiarandini, M. Manfrin, M. Mastrolilli, L. Paquete, O. Rossi-Doria, and T. Schiavinotto (2006). Hybrid metaheuristics for the vehicle routing problem with stochastic demands. [PDF] Journal of Mathematical Modelling and Algorithms, 5(1):91-110 [139 citations]

[P26] M. Manfrin, M. Birattari, T. Stützle, and M. Dorigo (2006). Parallel ant colony optimization for the traveling salesman problem. [PDF] In M. Dorigo, L. M. Gambardella, M. Birattari, A. Martinoli, R. Poli, and T. Stützle (Eds.) Ant Colony Optimization and Swarm Intelligence, 5th International Workshop, ANTS 2006, LNCS 4150 pp. 224-234. Springer, Berlin, Germany [137 citations]

[J30] C. Pinciroli, V. Trianni, R. O'Grady, G. Pini, A. Brutschy, M. Brambilla, N. Mathews, E. Ferrante, G. Di Caro, F. Ducatelle, M. Birattari, L. M. Gambardella, and M. Dorigo (2012).   ARGoS: a modular, multi-engine simulator for heterogeneous swarm robotics.[PDF]   Swarm Intelligence, 6(4):271-295 [132 citations]

[P08] M. Birattari, G. Bontempi, and H. Bersini (1999). Lazy learning meets the recursive least squares algorithm. [PDF] In M.S. Kearns, S.A. Solla, and D.A. Cohn (Eds.) NIPS'98: Advances in Neural Information Processing Systems 11. pp. 375-381. MIT Press, Cambridge, MA, USA [114 citations]

[C09] T. Stützle, M. López-Ibañez, P. Pellegrini, M. Maur, M. Montes de Oca, M. Birattari, and M. Dorigo (2012).   Parameter adaptation in ant colony optimization.   In Y. Hamadi, E. Monfroy, and F. Saubion (Eds.) Autonomous Search, pp. 191-215. Springer, Berlin, Germany [103 citations]

[J14] M. Birattari, P. Pellegrini, and M. Dorigo (2007).   On the invariance of ant colony optimization. [PDF]   IEEE Transactions on Evolutionary Computation, 11(6):732-742 [96 citations]

[P20] M. Birattari, G. Di Caro, and M. Dorigo (2002). Toward the formal foundation of ant programming. [PDF] In M. Dorigo, G. Di Caro, and M. Samples (Eds.) Ant Algorithms. Third International workshop, ANTS 2002. LNCS 2463, pp. 188-201, Springer, Berlin, Germany [89 citations]

[J03] G. Bontempi, H. Bersini, and M. Birattari (2001). The local paradigm for modeling and control: From neuro-fuzzy to lazy learning. [PDF] Fuzzy Sets and Systems, 121(1):59-72 [89 citations]

[J27] M. Montes de Oca, E. Ferrante, A. Scheidler, C. Pinciroli, M. Birattari, and M. Dorigo (2011).   Majority-rule opinion dynamics with differential latency: A mechanism for self-organized collective decision-making.[PDF]   Swarm Intelligence, 5(3/4):305-327 [62 citations]

[P22] L. Bianchi, M. Birattari, M. Chiarandini, M. Manfrin, M. Mastrolilli, L. Paquete, O. Rossi-Doria, and T. Schiavinotto (2004). Metaheuristics for the vehicle routing problem with stochastic demands. [PDF] In X. Yao, E. Burke, J. A. Lozano, J. Smith, J. J. Merelo-Guervós, J. A. Bullinaria, J. Rowe, P. Tino, A. Kabán, and H.-P. Schwefel (Eds.) Parallel Problem Solving from Nature - PPSN VIII, 8th International Conference. LNCS 3242, pp. 450-460. Springer, Berlin, Germany [62 citations]

[J22] C. Twomey, T. Stützle, M. Dorigo, M. Manfrin, and M. Birattari (2010).   An analysis of communication policies for homogeneous multi-colony ACO algorithms. [PDF]   Information Sciences, 180(12):2390-2404 [57 citations]

[P09] G. Bontempi, M. Birattari, and H. Bersini (1999). Local learning for iterated time-series prediction. [PDF] In I. Bradko and S. Dzeroski (Eds.) ICML'99: International Conference on Machine Learning, pp. 32-38. Morgan Kaufmann, San Francisco, CA, USA [55 citations]

[J21] P. Balaprakash, M. Birattari, T. Stützle, Z. Yuan, and M. Dorigo (2009).   Estimation-based ant colony optimization and local search for the probabilistic traveling salesman problem. [PDF]   Swarm Intelligence, 3(3):223-242 [51 citations]

[J16] A. L. Christensen, R. O'Grady, M. Birattari, and M. Dorigo (2008).   Fault detection in autonomous robots based on fault injection and learning. [PDF]   Autonomous Robots, 24(1):49-67 [50 citations]

[R018] M. Birattari, L. Paquete, T. Stützle, and K. Varrentrapp (2001).   Classification of Metaheuristics and Design of Experiments for the Analysis of Components.   Technical Report AIDA-01-05.   Intellektik, Technische Universität Darmstadt, Darmstadt, Germany [50 citations]

[J18] M. Birattari, P. Balaprakash, T. Stützle, and M. Dorigo (2008).   Estimation-based local search for stochastic combinatorial optimization using delta evaluations: A case study on the probabilistic traveling salesman problem. [PDF]   INFORMS Journal on Computing, 20(4):644-658 [49 citations]

[J41] M. Dorigo, M. Birattari, M. Brambilla (2014).   Swarm robotics.   Scholarpedia, 9(1):1463 [47 citations]

[J13] M. Birattari and M. Dorigo (2007).   How to assess and report the performance of a stochastic algorithm on a benchmark problem: Mean or best result on a number of runs? [PDF]   Optimization Letters, 1(3):309-311 [47 citations]

[P24] M. Birattari, P. Balaprakash, and M. Dorigo (2005).   ACO/F-Race: Ant colony optimization and racing techniques for combinatorial optimization under uncertainty. [PDF]   In K. F. Doerner, M. Gendreau, P. Greistorfer, W. J. Gutjahr, R. F. Hartl, and M. Reimann (Eds.) MIC 2005: The 6th Metaheuristics International Conference, pp. 107-112 [46 citations]

[P29] A. Campo, S. Nouyan, M. Birattari, R. Groß, and M. Dorigo (2006).   Negotiation of goal direction for cooperative transport. [PDF]   In M. Dorigo, L. M. Gambardella, M. Birattari, A. Martinoli, R. Poli, and T. Stützle (Eds.) Ant Colony Optimization and Swarm Intelligence, 5th International Workshop, ANTS 2006, LNCS 4150 pp. 191-202. Springer, Berlin, Germany [44 citations]

[P02] G. Bontempi, M. Birattari, and H. Bersini (1998).   Recursive lazy learning for modeling and control. [PDF]   In C. Nédellec and C. Rouveirol (Eds.) Machine Learning: ECML-98. 10th European Conference on Machine Learning. LNCS 1398, pp. 292-303. Springer, Berlin, Germany [44 citations]

[J55] M. López-Ibáñez, J. Dubois-Lacoste, L. Pérez Cáceres, M. Birattari, and T. Stützle (2016).   The irace package: Iterated racing for automatic algorithm configuration.[PDF]   Operations Research Perspectives, 3:43--58 [42 citations]

[J44] G. Francesca, M. Brambilla, A. Brutschy, V. Trianni, and M. Birattari (2014).   AutoMoDe: A novel approach to the automatic design of control software for robot swarms.[PDF]   Swarm Intelligence, 8(2):89-112 [41 citations]

[J39] A. Brutschy, G. Pini, C. Pinciroli, M. Birattari, and M. Dorigo (2014).   Self-organized task allocation to sequentially interdependent tasks in swarm robotics.[PDF]   Autonomous Agents and Multi-Agent Systems, 28(1):101-125 [41 citations]

[J26] G. Pini, A. Brutschy, M. Frison, A. Roli, M. Dorigo, and M. Birattari (2011).   Task partitioning in swarms of robots: An adaptive method for strategy selection.[PDF]   Swarm Intelligence, 5(3/4):283-304 [41 citations]

Last update: Jul 16, 2017