Most cited publications
My h-index is 54. The following are my fifty-three 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.
IEEE Computational Intelligence Magazine, 1(4):28-391
[16273 citations]
[J33] M. Brambilla, E. Ferrante, M. Birattari, and M. Dorigo (2013).
Swarm robotics: A review from the swarm engineering perspective.
Swarm Intelligence,
7(1):1-41
[1733 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.
Operations Research Perspectives,
3:43--58
[1689 citations]
[P18] M. Birattari, T. Stützle, L. Paquete, and K. Varrentrapp (2002).
A racing algorithm for configuring metaheuristics.
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
[782 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.
Swarm Intelligence,
6(4):271-295
[582 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 [503 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 [497 citations]
[B02] M. Birattari (2009). Tuning Metaheuristics: A machine learning perspective. Springer, Berlin, Germany [470 citations]
[J20] M. A. Montes de Oca, T. Stützle, M. Birattari, and M. Dorigo (2009).
Frankenstein's PSO: A composite particle swarm optimization
algorithm.
IEEE Transactions on Evolutionary Computation,
13(5):1120-1132
[394 citations]
[J05] M. Zlochin, M. Birattari, N. Meuleau, and M. Dorigo (2004).
Model-based search for combinatorial optimization:
A critical survey.
Annals of Operations Research,
131: 373-395
[357 citations]
[J01] G. Bontempi, M. Birattari, and H. Bersini (1999).
Lazy learning for local modeling and control design.
International Journal of Control,
72(7/8):643-658
[336 citations]
[J15] M. Dorigo and M. Birattari (2007).
Swarm Intelligence.
Scholarpedia,
2(9):1462
[321 citations]
[P37] P. Balaprakash, M. Birattari, T. Stützle (2007).
Improvement strategies for the F-Race algorithm:
Sampling design and iterative refinement.
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
[311 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.
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
[306 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 [230 citations]
[J10] M. Chiarandini, M. Birattari, K. Socha, and O. Rossi-Doria (2006).
An effective hybrid algorithm for
university course timetabling.
Journal of Scheduling,
9(5):403-432
[230 citations]
[T03] M. Birattari (2004).
The Problem of Tuning Metaheuristics
as Seen from a Machine
Learning Perspective.
PhD Thesis, Université Libre de
Bruxelles.
[196 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.
Journal of Mathematical Modelling and Algorithms,
5(1):91-110
[190 citations]
[J41] M. Dorigo, M. Birattari, M. Brambilla (2014). Swarm robotics. Scholarpedia, 9(1):1463 [184 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.
Swarm Intelligence, 8(2):89-112
[177 citations]
[P26] M. Manfrin, M. Birattari, T. Stützle, and M. Dorigo (2006).
Parallel ant colony optimization for the traveling salesman
problem.
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
[177 citations]
[P08] M. Birattari, G. Bontempi, and H. Bersini (1999).
Lazy learning meets the recursive least squares algorithm.
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
[159 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.
Swarm Intelligence,
5(3/4):305-327
[146 citations]
[J39] A. Brutschy, G. Pini, C. Pinciroli, M. Birattari, and M. Dorigo (2014).
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Self-organized task allocation to sequentially interdependent tasks in swarm robotics.
Autonomous Agents and Multi-Agent Systems, 28(1):101-125
[144 citations]
[J14] M. Birattari, P. Pellegrini, and M. Dorigo (2007).
On the invariance of ant colony optimization.
IEEE Transactions on Evolutionary Computation,
11(6):732-742
[133 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 [128 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.
Autonomous Robots,
24(1):49-67
[119 citations]
[J03] G. Bontempi, H. Bersini, and M. Birattari (2001).
The local paradigm for modeling and control:
From neuro-fuzzy to lazy learning.
Fuzzy Sets and Systems,
121(1):59-72
[115 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 [109 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.
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
[101 citations]
[P20] M. Birattari, G. Di Caro, and M. Dorigo (2002).
Toward the formal foundation of ant programming.
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
[101 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.
Swarm Intelligence,
9(2/3):125-152
[98 citations]
[C06] M. Dorigo and M. Birattari (2010).
Ant Colony Optimization.
In C. Sammut and G. Webb Encyclopedia of Machine
Learning, pp. 37-40, Springer, Berlin, Germany
[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.
Information Sciences,
180(12):2390-2404
[91 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.
ACM Transactions on Autonomous and Adaptive Systems,
9(4):17/1-17/28
[90 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.
Swarm Intelligence,
5(3/4):283-304
[85 citations]
[P60] M. Brambilla; C. Pinciroli; M. Birattari; and M. Dorigo (2012).
Property-driven design for swarm robotics.
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
[76 citations]
[P56] A. Roli, M. Manfroni, C. Pinciroli, and M. Birattari (2011).
On the design of Boolean network robots.
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
[74 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.
Natural Computing,
13(2):225-245
[73 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.
Swarm Intelligence,
6(1):49-75
[73 citations]
[J56] L. Garattoni and M. Birattari (2018). Autonomous task sequencing in a robot swarm. Science Robotics, 3(20):eaat0430 [72 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.
Swarm Intelligence,
3(3):223-242
[71 citations]
[P09] G. Bontempi, M. Birattari, and H. Bersini (1999).
Local learning for iterated time-series prediction.
In I. Bradko and S. Dzeroski (Eds.)
ICML'99:
International Conference on Machine Learning,
pp. 32-38.
Morgan Kaufmann, San Francisco, CA, USA
[70 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?
Optimization Letters,
1(3):309-311
[69 citations]
[P29] A. Campo, S. Nouyan, M. Birattari, R. Groß, and M. Dorigo (2006).
Negotiation of goal direction for cooperative transport.
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
[65 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.
INFORMS Journal on Computing,
20(4):644-658
[63 citations]
[P24] M. Birattari, P. Balaprakash, and M. Dorigo (2005).
ACO/F-Race: Ant colony optimization and racing techniques
for combinatorial optimization under uncertainty.
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
[62 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.
IEEE Transactions on Industrial Electronics,
52(1):280-290
[60 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?
Technical Report TR/IRIDIA/2004-01.
IRIDIA, Université Libre de Bruxelles, Belgium
[59 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 [58 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.
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
[57 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.
Adaptive Behavior,
21(2):118-136
[56 citations]
[J28] P. Pellegrini, T. Stützle, M. Birattari (2012).
A critical analysis of parameter adaptation in ant colony optimization.
Swarm Intelligence,
6(1):23-48
[55 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.
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
[54 citations]
Last update: Jun 11, 2023