Most cited papers in Metaheuristic Optimization Algorithms Research
What are the most cited papers in Metaheuristic Optimization Algorithms Research?
The most cited paper in Metaheuristic Optimization Algorithms Research is "A fast and elitist multiobjective genetic algorithm: NSGA-II" (Kalyanmoy Deb, Amrit Pratap, Sakshi Agarwal et al., 2002), with 49,664 citations. Next come "Particle swarm optimization" (48,693) and "Statistical Learning Theory" (26,900).
Showing 50 of 100 papers. Every paper with more than 2,276 citations is listed.
| # | Paper | ||
|---|---|---|---|
| 1 | A fast and elitist multiobjective genetic algorithm: NSGA-II Kalyanmoy Deb, Amrit Pratap, Sakshi Agarwal et al. · IEEE Transactions on Evolutionary Computation | Apr 2002 | 49,664 |
| 2 | Particle swarm optimization James C. Kennedy, R.C. Eberhart | 19 Nov 2002 | 48,693 |
| 3 | Statistical Learning Theory Yuhai Wu, Vladimir N. Vapnik · Technometrics | Nov 1999 | 26,900 |
| 4 | Particle swarm optimization Riccardo Poli, James C. Kennedy, Tim Blackwell · Swarm Intelligence | 31 Jul 2007 | 21,401 |
| 5 | Grey Wolf Optimizer Seyedali Mirjalili, Seyed Mohammad Mirjalili, Seyed Mohammad Mirjalili et al. · Advances in Engineering Software | 21 Jan 2014 | 19,320 |
| 6 | A new optimizer using particle swarm theory R.C. Eberhart, James C. Kennedy | 19 Nov 2002 | 15,000 |
| 7 | The Whale Optimization Algorithm Seyedali Mirjalili, Andrew W. Lewis · Advances in Engineering Software | 26 Feb 2016 | 14,627 |
| 8 | No free lunch theorems for optimization David H. Wolpert, William G. Macready · IEEE Transactions on Evolutionary Computation | Apr 1997 | 14,318 |
| 9 | Ant system: optimization by a colony of cooperating agents Marco Dorigo, Vittorio Maniezzo, A. Colorni · IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) | Feb 1996 | 12,083 |
| 10 | A modified particle swarm optimizer Yibing Shi, R.C. Eberhart | 27 Nov 2002 | 10,246 |
| 11 | MOEA/D: A Multiobjective Evolutionary Algorithm Based on Decomposition Qingfu Zhang, Hui Li · IEEE Transactions on Evolutionary Computation | 29 Nov 2007 | 10,000 |
| 12 | The particle swarm - explosion, stability, and convergence in a multidimensional complex space Maurice Clerc, James C. Kennedy · IEEE Transactions on Evolutionary Computation | 2002 | 9,039 |
| 13 | Reinforcement Learning: A Survey Leslie Pack Kaelbling, Michael L. Littman, Andrew Moore · Journal of Artificial Intelligence Research | May 1996 | 8,975 |
| 14 | Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach Eckart Zitzler, Lothar Thiele · IEEE Transactions on Evolutionary Computation | 1999 | 8,815 |
| 15 | Optuna Takuya Akiba, Shotaro Sano, Toshihiko Yanase et al. | 25 Jul 2019 | 8,344 |
| 16 | Ant colony system: a cooperative learning approach to the traveling salesman problem Marco Dorigo, Luca Maria Gambardella · IEEE Transactions on Evolutionary Computation | Apr 1997 | 8,098 |
| 17 | Random search for hyper-parameter optimization James Bergstra, Yoshua Bengio, Léon Bottou | 2012 | 7,930 |
| 18 | A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm Derviş Karaboğa, Bahriye Basturk · Journal of Global Optimization | 13 Apr 2007 | 7,669 |
| 19 | GSA: A Gravitational Search Algorithm Esmat Rashedi, Hossein Nezamabadi–pour, Saeı̈d Saryazdi · Information Sciences | 17 Mar 2009 | 7,418 |
| 20 | An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints Kalyanmoy Deb, Himanshu Jain · IEEE Transactions on Evolutionary Computation | 16 Sep 2013 | 7,153 |
| 21 | Muiltiobjective Optimization Using Nondominated Sorting in Genetic Algorithms N. Srinivas, Kalyanmoy Deb · Evolutionary Computation | Sep 1994 | 6,944 |
| 22 | Ant Colony Optimization Teofilo F. Gonzalez | 15 May 2007 | 6,658 |
| 23 | Harris hawks optimization: Algorithm and applications Ali Asghar Heidari, Seyedali Mirjalili, Hossam Faris et al. · Future Generation Computer Systems | 28 Feb 2019 | 6,334 |
| 24 | Cuckoo Search via Lévy flights Xin‐She Yang, Suash Deb | 2009 | 6,178 |
| 25 | “Neural” computation of decisions in optimization problems J. J. Hopfield, David W. Tank · Biological Cybernetics | Jul 1985 | 6,065 |
| 26 | SCA: A Sine Cosine Algorithm for solving optimization problems Seyedali Mirjalili · Knowledge-Based Systems | 6 Jan 2016 | 5,733 |
| 27 | Comparison of Multiobjective Evolutionary Algorithms: Empirical Results Eckart Zitzler, Kalyanmoy Deb, Lothar Thiele · Evolutionary Computation | Jun 2000 | 5,711 |
| 28 | Tabu Search—Part II Fred Glover · INFORMS journal on computing | Feb 1990 | 5,669 |
| 29 | A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms Joaquín Derrac, Salvador García, Daniel Molina et al. · Swarm and Evolutionary Computation | Mar 2011 | 5,536 |
| 30 | Ant colony optimization Marco Dorigo, Mauro Birattari, Thomas Stützle · IEEE Computational Intelligence Magazine | Nov 2006 | 5,332 |
| 31 | Differential Evolution: A Survey of the State-of-the-Art Swagatam Das, Ponnuthurai Nagaratnam Suganthan · IEEE Transactions on Evolutionary Computation | 19 Oct 2010 | 5,321 |
| 32 | A Fast Elitist Non-dominated Sorting Genetic Algorithm for Multi-objective Optimization: NSGA-II Kalyanmoy Deb, Samir G. Agrawal, Amrit Pratap et al. · Lecture notes in computer science | 2000 | 5,282 |
| 33 | Teaching–learning-based optimization: A novel method for constrained mechanical design optimization problems R. Venkata Rao, Vimal J. Savsani, Dipak P. Vakharia · Computer-Aided Design | 8 Jan 2011 | 5,174 |
| 34 | Salp Swarm Algorithm: A bio-inspired optimizer for engineering design problems Seyedali Mirjalili, Seyedali Mirjalili, Amir H. Gandomi et al. · Advances in Engineering Software | 25 Jul 2017 | 5,118 |
| 35 | A New Metaheuristic Bat-Inspired Algorithm Xin‐She Yang · Studies in computational intelligence | 2010 | 4,794 |
| 36 | A discrete binary version of the particle swarm algorithm James C. Kennedy, R.C. Eberhart | 22 Nov 2002 | 4,767 |
| 37 | Survey of multi-objective optimization methods for engineering R. Timothy Marler, Jasbir Singh Arora · Structural and Multidisciplinary Optimization | 22 Mar 2004 | 4,728 |
| 38 | Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm Seyedali Mirjalili · Knowledge-Based Systems | 18 Jul 2015 | 4,658 |
| 39 | A review on genetic algorithm: past, present, and future Sourabh Katoch, Sumit Singh Chauhan, Vijay Kumar · Multimedia Tools and Applications | 31 Oct 2020 | 4,634 |
| 40 | A genetic algorithm tutorial Darrell Whitley · Statistics and Computing | Jun 1994 | 4,575 |
| 41 | Handling multiple objectives with particle swarm optimization Carlos A. Coello Coello, G.T. Pulido, M.S. Lechuga · IEEE Transactions on Evolutionary Computation | Jun 2004 | 4,471 |
| 42 | Completely Derandomized Self-Adaptation in Evolution Strategies Nikolaus Hansen, Andreas Ostermeier · Evolutionary Computation | Jun 2001 | 4,414 |
| 43 | Performance assessment of multiobjective optimizers: an analysis and review Eckart Zitzler, Lothar Thiele, Marco Laumanns et al. · IEEE Transactions on Evolutionary Computation | Apr 2003 | 4,344 |
| 44 | Biogeography-Based Optimization D. Simon · IEEE Transactions on Evolutionary Computation | 4 Aug 2008 | 4,332 |
| 45 | Particle swarm optimization: developments, applications and resources Eberhart, Yuhui Shi | 2001 | 4,324 |
| 46 | Variable neighborhood search Nenad Mladenović, Pierre Hansen · Computers & Operations Research | Nov 1997 | 4,232 |
| 47 | Future paths for integer programming and links to artificial intelligence Fred Glover · Computers & Operations Research | 1986 | 4,164 |
| 48 | A new approach to variable metric algorithms Roger Fletcher · The Computer Journal | Mar 1970 | 4,132 |
| 49 | Firefly Algorithms for Multimodal Optimization Xin‐She Yang · Lecture notes in computer science | 2009 | 4,098 |
| 50 | Empirical study of particle swarm optimization Yibing Shi, R.C. Eberhart | 20 Jan 2003 | 3,958 |
Citations are OpenAlex's own counts, from its 2026-09-23 snapshot, so the ranking can differ from Google Scholar or Web of Science. A paper is listed for a field when OpenAlex files it under one of the field's topics; retracted papers and papers whose citation count cannot be traced to citing works are left out, and a preprint and the article it became are shown once. Release dates are OpenAlex's: where a source gave only a month or a year, that is what is shown. How the lists are chosen.