Most cited publications

My h-index is 55. The following are my fifty-five 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):28-391 [17046 citations]

[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 [1894 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 [1886 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 [815 citations] — Winner of the 2012 SIGEVO Impact Award

[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 [640 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 [537 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 [537 citations]

[B02] M. Birattari (2009). Tuning Metaheuristics: A machine learning perspective. Springer, Berlin, Germany [497 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 [411 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 [367 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 [343 citations]

[J15] M. Dorigo and M. Birattari (2007).   Swarm Intelligence. [PDF]   Scholarpedia, 2(9):1462 [342 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 [325 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 [313 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 [242 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 [238 citations]

[J41] M. Dorigo, M. Birattari, M. Brambilla (2014).   Swarm robotics.   Scholarpedia, 9(1):1463 [208 citations]

[T03] M. Birattari (2004).   The Problem of Tuning Metaheuristics as Seen from a Machine Learning Perspective. [PDF]   PhD Thesis, Université Libre de Bruxelles. [198 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 [194 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 [193 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 [189 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 [162 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 [158 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 [154 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 [138 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 [136 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 [130 citations]

[J54] G. Francesca and M. Birattari (2016).   Automatic design of robot swarms: achievements and challenges.   Frontiers in Robotics and AI, 3(29):1-9 [120 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 [117 citations]

[J52] G. Francesca, M. Brambilla, A. Brutschy, L. Garattoni, R. Miletitch, G. Podevijn, A. Reina, T. Soleymani, M. Salvaro, C. Pinciroli, F. Mascia, V. Trianni, and M. Birattari (2015).   AutoMoDe-Chocolate: automatic design of control software for robot swarms.[PDF]   Swarm Intelligence, 9(2/3):125-152 [110 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 [105 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 [103 citations]

[C06] M. Dorigo and M. Birattari (2010).   Ant Colony Optimization. [PDF]   In C. Sammut and G. Webb Encyclopedia of Machine Learning, pp. 37-40, Springer, Berlin, Germany [98 citations]

[J46] M. Brambilla, A. Brutschy, M. Dorigo, and M. Birattari (2014).   Property-driven design for robot swarms: A design method based on prescriptive modeling and model checking.[PDF]   ACM Transactions on Autonomous and Adaptive Systems, 9(4):17/1-17/28 [96 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 [95 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 [95 citations]

[J56] L. Garattoni and M. Birattari (2018).   Autonomous task sequencing in a robot swarm.   Science Robotics, 3(20):eaat0430 [84 citations]

[J42] E. Ferrante, A.E. Turgut, A. Stranieri, C. Pinciroli, M. Birattari, and M. Dorigo (2014).   A self-adaptive communication strategy for flocking in stationary and non-stationary environments.[PDF]   Natural Computing, 13(2):225-245 [79 citations]

[P60] M. Brambilla; C. Pinciroli; M. Birattari; and M. Dorigo (2012).   Property-driven design for swarm robotics. [PDF]   In V. Conitzer, M. Winikoff, L. Padgham, and W. van der Hoek (Eds.) Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2012, pp.139-146. IFAAMAS [79 citations]

[J29] Z. Yuan, M. Montes de Oca, M. Birattari, and T. Stützle (2012).   Continuous optimization algorithms for tuning real and integer parameters of swarm intelligence algorithms.[PDF]   Swarm Intelligence, 6(1):49-75 [77 citations]

[P56] A. Roli, M. Manfroni, C. Pinciroli, and M. Birattari (2011).   On the design of Boolean network robots. [PDF]   In C. Di Chio, A. Brabazon, G.A. Di Caro, R. Drechsler, M. Farooq, J. Grahl, G. Greenfield, C. Prins, J. Romero, G. Squillero, E. Tarantino, A.G.B. Tettamanzi, N. Urquhart, and A.S. Uyar (Eds.) Applications of Evolutionary Computation, EvoApplications 2011: EvoCOMPLEX, EvoGAMES, EvoIASP, EvoINTELLIGENCE, EvoNUM, and EvoSTOC, LNCS 6624/5, pp. 43-52. Springer. Berlin, Germany [76 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 [74 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 [72 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 [71 citations]

[J57] M. Birattari, A. Ligot, D. Bozhinoski, M. Brambilla, G. Francesca, L. Garattoni, D. Garzón Ramos, K. Hasselmann, M. Kegeleirs, J. Kuckling, F. Pagnozzi, A. Roli, M. Salman, and T. Stützle (2019).   Automatic off-line design of robot swarms: a manifesto.   Frontiers in Robotics and AI, 6:59 [70 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 [67 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 [65 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 [64 citations]

[J06] D. Villacci, G. Bontempi, A. Vaccaro, and M. Birattari (2005).   The role of learning methods in the dynamic assessment of power components loading capability. [PDF]   IEEE Transactions on Industrial Electronics, 52(1):280-290 [64 citations]

[P62] G. Francesca, M. Brambilla, V. Trianni, M. Dorigo, and M. Birattari (2012).   Analysing an evolved robotic behaviour using a biological model of collegial decision making. [PDF]   In T. Ziemke, C. Balkenius, and J. Hallam (Eds.) From Animals to Animats 12: 12th International Conference on Simulation of Adaptive Behavior, SAB 2012, LNAI 7426, pp. 381-390. Springer. Berlin, Germany [63 citations]

[R032] M. Birattari (2004).   On the estimation of the expected performance of a metaheuristic on a class of instances. How many instances, how many runs? [PDF]   Technical Report TR/IRIDIA/2004-01.   IRIDIA, Université Libre de Bruxelles, Belgium [60 citations]

[J28] P. Pellegrini, T. Stützle, M. Birattari (2012).   A critical analysis of parameter adaptation in ant colony optimization.[PDF]   Swarm Intelligence, 6(1):23-48 [59 citations]

[R124] L. Garattoni, G. Francesca, A. Brutschy, C. Pinciroli, and M. Birattari (2015).   Software Infrastructure for E-puck (and TAM).[PDF]   Technical Report TR/IRIDIA/2015-004.   IRIDIA, Université Libre de Bruxelles, Belgium [56 citations]

[J36] G. Pini, A. Brutschy, C. Pinciroli, M. Dorigo, and M. Birattari (2013).   Autonomous task partitioning in robot foraging: an approach based on cost estimation.[PDF]   Adaptive Behavior, 21(2):118-136 [56 citations]

[P52] E. Ferrante, A. E. Turgut, N. Mathews, M. Birattari, and M. Dorigo (2010).   Flocking in stationary and non-stationary environments: A novel communication strategy for heading alignment. [PDF]   In R. Schaefer, C. Cotta, J. Kolodziej, and G. Rudolph (Eds.) Parallel Problem Solving from Nature, PPSN XI: 11th International Conference, LNCS 6239, pp. 331-340, Springer. Berlin, Germany [56 citations]

Last update: Feb 8, 2024