Talk:Metaheuristic/List of Metaheuristics
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Untitled[edit]
Due to the nature of research, there are constantly new metaheuristics. Below is a list of metaheuristics:
- 1952: Robbins and Monro work on stochastic optimization methods.[1]
- 1952: Fermi and Metropolis develop an early form of pattern search as described belatedly by Davidon.[2]
- 1954: Barricelli carry out the first simulations of the evolution process and use them on general optimization problems.[3]
- 1963: Rastrigin proposes random search.[4]
- 1965: Matyas proposes random optimization.[5]
- 1965: Rechenberg proposes evolution strategy.[6]|
- 1965: Nelder and Mead propose a simplex heuristic, which was shown by Powell to converge to non-stationary points on some problems.[7]
- 1966: Fogel et al. propose evolutionary programming.[8]
- 1970: Hastings proposes the Metropolis-Hastings algorithm.[9]
- 1970: Cavicchio proposes adaptation of control parameters for an optimizer.[10]
- 1970: Kernighan and Lin propose a graph partitioning method, related to variable-depth search and prohibition-based (tabu) search.[11]
- 1975: Holland proposes the genetic algorithm.[12]
- 1977: Glover proposes Scatter Search.[13]
- 1978: Mercer and Sampson propose a metaplan for tuning an optimizer's parameters by using another optimizer.[14]
- 1980: Smith describes genetic programming.[15]
- 1983: Kirkpatrick et al. propose simulated annealing.[16]
- 1986: Glover proposes tabu search, first mention of the term metaheuristic.[17]
- 1986: Farmer et al. work on the artificial immune system.[18]
- 1986: Grefenstette proposes another early form of metaplan for tuning an optimizer's parameters by using another optimizer.[19]
- 1988: First conference on genetic algorithms is organized at the University of Illinois at Urbana-Champaign.
- 1988: Koza registers his first patent on genetic programming.[20][21]
- 1989: Goldberg publishes a well known book on genetic algorithms.[22]
- 1989: Evolver, the first optimization software using the genetic algorithm.
- 1989: Moscato proposes the memetic algorithm.[23]
- 1991: Interactive evolutionary computation.
- 1992: Dorigo proposes the ant colony algorithm.[24]
- 1993: The journal, Evolutionary Computation, begins publication by the Massachusetts Institute of Technology.
- 1993: Fonseca and Fleming propose MOGA for multiobjective optimization.[25]
- 1994: Battiti and Tecchiolli propose Reactive Search Optimization(RSO) principles for the online self-tuning of heuristics.[26][27]
- 1994: Srinivas and Deb propose NSGA for multiobjective optimization.[28]
- 1995: Kennedy and Eberhart propose particle swarm optimization.[29]
- 1995: Wolpert and Macready prove the no free lunch theorems.[30][31][32][33][34][35][36][37][38][39][40]
- 1996: Mühlenbein and Paaß work on the estimation of distribution algorithm.[41]
- 1996: Hansen and Ostermeier propose CMA-ES.[42][43][44]
- 1997: Storn and Price propose differential evolution.[45]
- 1997: Rubinstein proposes the cross entropy method.[46]
- 1999: Taillard and Voss propose POPMUSIC.[47]
- 2001: Geem et al. propose harmony search.[48]
- 2001: Hanseth and Aanestad introduce the Bootstrap Algorithm.[49]
- 2002: Deb et al. propose NSGA-II for multiobjective optimization.[50]
- 2002 Han and Kim propose QEA for a class of combinatorial optimization.[51]
- 2004: Nakrani and Tovey propose bees optimization.[52]
- 2005: Krishnanand and Ghose propose Glowworm swarm optimization.[53][54][55]
- 2005: Karaboga proposes Artificial Bee Colony Algorithm (ABC).[56]
- 2005: Duc-Truong Pham et al. proposed Bees Algorithms (BA)
- 2006: Haddad et al. introduces honey-bee mating optimization.[57]
- 2007: Hamed Shah-Hosseini introduces Intelligent Water Drops.
- 2007: Atashpaz-Gargari introduces Imperialist competitive algorithm.
- 2008: Wierstra et al. propose natural evolution strategies based on the natural gradient.[58]
- 2008: Yang introduces firefly algorithm.[59]
- 2008: Mucherino and Seref propose the Monkey Search
- 2009: Ali Husseinzadeh Kashan introduced the League Championship Algorithm (LCA).[60][61][62]
- 2009: Kadioglu and Sellmann introduce Hegel and Fichte's dialectic as a local search meta-heuristic Dialectic Search.[63]
- 2009: Yang and Deb introduce cuckoo search.[64]
- 2009: Rashedi proposes Gravitational Search Algorithm
- 2009: Josue Cuevas et al. propose Virus Optimization Algorithm
- 2010: Yang develops bat algorithm.[65]
- 2011: Hamed Shah-Hosseini proposes the Galaxy-based Search Algorithm.[66]
- 2011: Tamura and Yasuda propose spiral optimization.[67][68]
- 2012: Civicioglu proposes Differential Search Algorithm. Matlab code-link has been provided in Çivicioglu, P.,(2012).[69] and Matlab File Exchange.
- 2013: Civicioglu proposes Artificial Cooperative Search Algorithm (ACS) [70].
- 2015: Election Algorithm: A new socio-politically inspired strategy — Preceding unsigned comment added by 2.187.47.244 (talk) 07:31, 23 June 2016 (UTC)
- 2015: Tsai proposes Search Economics (SE). [71]
- 2016: Yazdani and Jolai propose Lion Optimization Algorithm — Preceding unsigned comment added by Yazdanimaziar (talk • contribs) 14:38, 27 April 2018 (UTC)
- 2017: Kuo proposes Entanglement-QTS [72]
- 2017: Bouchekara developed the Most Valuable Player Algorithm (MVPA) [73].: — Preceding unsigned comment added by Bouchekara (talk • contribs) 05:47, 14 March 2018 (UTC) — Preceding unsigned comment added by 61.224.89.3 (talk) 08:13, 20 June 2020 (UTC)
- 2018: Chou proposes Jaguar Algorithm (JA) [74]
Also see[edit]
References[edit]
- ^ Robbins, H.; Monro, S. (1951). "A Stochastic Approximation Method". Annals of Mathematical Statistics. 22 (3): 400–407. doi:10.1214/aoms/1177729586.
- ^ Davidon, W.C. (1991). "Variable metric method for minimization". SIAM Journal on Optimization. 1 (1): 1–17. doi:10.1137/0801001.
- ^ Barricelli, N.A. (1954). "Esempi numerici di processi di evoluzione". Methodos: 45–68.
- ^ Rastrigin, L.A. (1963). "The convergence of the random search method in the extremal control of a many parameter system". Automation and Remote Control. 24 (10): 1337–1342.
- ^ Matyas, J. (1965). "Random optimization". Automation and Remote Control. 26 (2): 246–253.
- ^ Rechenberg, I. (1965). Cybernetic Solution Path of an Experimental Problem. Royal Aircraft Establishment Library Translation.
- ^ Nelder, J.A.; Mead, R. (1965). "A simplex method for function minimization". Computer Journal. 7: 308–313. doi:10.1093/comjnl/7.4.308.
- ^ Fogel, L.; Owens, A.J.; Walsh, M.J. (1966). Artificial Intelligence through Simulated Evolution. Wiley. ISBN 0-471-26516-0.
- ^ Hastings, W.K. (1970). "Monte Carlo Sampling Methods Using Markov Chains and Their Applications". Biometrika. 57 (1): 97–109. doi:10.1093/biomet/57.1.97.
- ^ Cavicchio, D.J. (1970). "Adaptive search using simulated evolution". Technical Report. University of Michigan, Computer and Communication Sciences Department. hdl:2027.42/4042.
- ^
Kernighan, B.W.;Lin, S. (1970). "An efficient heuristic procedure for partitioning graphs". Bell System Technical Journal. 49 (2): 291–307.
{{cite journal}}: CS1 maint: multiple names: authors list (link) - ^ Holland, J.H. (1975). Adaptation in Natural and Artificial Systems. University of Michigan Press. ISBN 0-262-08213-6.
- ^ Glover, Fred (1977). "Heuristics for Integer programming Using Surrogate Constraints". Decision Sciences. 8 (1): 156–166.
- ^
Mercer, R.E. (1978). "Adaptive search using a reproductive metaplan". Kybernetes (The International Journal of Systems and Cybernetics). 7 (3): 215–228. doi:10.1108/eb005486.
{{cite journal}}: Unknown parameter|coauthors=ignored (|author=suggested) (help) - ^ Smith, S.F. (1980). A Learning System Based on Genetic Adaptive Algorithms (PhD Thesis). University of Pittsburgh.
- ^ Kirkpatrick, S.; Gelatt Jr., C.D.; Vecchi, M.P. (1983). "Optimization by Simulated Annealing". Science. 220 (4598): 671–680. doi:10.1126/science.220.4598.671. PMID 17813860.
- ^ Glover, F. (1986). "Future Paths for Integer Programming and Links to Artificial Intelligence". Computers and Operations Research. 13 (5): 533–549. doi:10.1016/0305-0548(86)90048-1.
- ^ Farmer, J.D.; Packard, N.; Perelson, A. (1986). "The immune system, adaptation and machine learning". Physica D. 22 (1–3): 187–204. doi:10.1016/0167-2789(86)90240-X.
- ^ Grefenstette, J.J. (1986). "Optimization of control parameters for genetic algorithms". IEEE Transactions Systems, Man, and Cybernetics. 16 (1): 122–128. doi:10.1109/TSMC.1986.289288.
- ^ US 4935877
- ^ Koza, J.R. (1992). Genetic Programming : on the programming of computers by means of natural selection. MIT Press. ISBN 0-262-11170-5.
- ^ Goldberg, D.E. (1989). Genetic Algorithms in Search, Optimization and Machine Learning. Kluwer Academic Publishers. ISBN 0-201-15767-5.
- ^ Moscato, P. (1989). "On Evolution, Search, Optimization, Genetic Algorithms and Martial Arts : Towards Memetic Algorithms". Technical Report C3P 826. Caltech Concurrent Computation Program.
- ^ Dorigo, M. (1992). Optimization, Learning and Natural Algorithms (Phd Thesis). Politecnico di Milano, Italie.
- ^ Fonseca, C.M.; Fleming, P.J. (1993). "Genetic Algorithms for Multiobjective Optimization: formulation, discussion and generalization". Proceedings of the 5th International Conference on Genetic Algorithms. Urbana-Champaign, IL, USA: 416–423.
- ^
Battiti, Roberto (1994). "The reactive tabu search" (PDF). ORSA Journal on Computing. 6 (2): 126–140.
{{cite journal}}: Cite has empty unknown parameter:|month=(help); Unknown parameter|coauthors=ignored (|author=suggested) (help) - ^
Battiti, Roberto (1995). "Training neural nets with the reactive tabu search" (PDF). IEEE Transactions on Neural Networks. 6 (5): 1185–1200. doi:10.1109/72.410361. PMID 18263407.
{{cite journal}}: Cite has empty unknown parameter:|month=(help); Unknown parameter|coauthors=ignored (|author=suggested) (help) - ^ Srinivas, N.; Deb, K. (1994). "Multiobjective Optimization Using Nondominated Sorting in Genetic Algorithms". Evolutionary Computation. 2 (3): 221–248. doi:10.1162/evco.1994.2.3.221.
- ^
Kennedy, J.; Eberhart, R. (1995). "Particle Swarm Optimization". Proceedings of IEEE International Conference on Neural Networks. Vol. IV. pp. 1942–1948.
{{cite conference}}: Unknown parameter|booktitle=ignored (|book-title=suggested) (help) - ^ Wolpert, D.H.; Macready, W.G. (1995). "No free lunch theorems for search". Technical Report SFI-TR-95-02-010. Santa Fe Institute.
- ^ Wolpert, D.H.; Macready, W.G. (1997). "No free lunch theorems for optimization". IEEE Transactions on Evolutionary Computation. 1 (1): 67–82. doi:10.1109/4235.585893.
- ^ David H. Wolpert (2001). "The supervised learning no-free-lunch Theorems". Proceedings 6th Online World Conference on Soft Computing in Industrial Applications. pp. 25–42. Retrieved 9 April, 2013.
{{cite book}}: Check date values in:|accessdate=(help) - ^ Wolpert, D.H., Macready, W.G. (2005). "Coevolutionary free lunches". IEEE Transactions on Evolutionary Computation. 9 (6): 721–735. doi:10.1109/TEVC.2005.856205. ISSN 1089-778X.
{{cite journal}}:|access-date=requires|url=(help); Check date values in:|accessdate=(help); Unknown parameter|month=ignored (help)CS1 maint: multiple names: authors list (link) - ^ Auger, Anne, Teytaud, Olivier (2007). "Continuous lunches are free!". Proceedings of the 9th annual conference on Genetic and evolutionary computation. GECCO '07. London, England: ACM. pp. 916–922. doi:10.1145/1276958.1277145. ISBN 978-1-59593-697-4. Retrieved 9 April, 2013.
{{cite book}}: Check date values in:|accessdate=(help)CS1 maint: multiple names: authors list (link) - ^ Auger, Anne, Teytaud, Olivier (2010). "Continuous Lunches Are Free Plus the Design of Optimal Optimization Algorithms". Algorithmica. 57 (1). Springer-Verlag: 121–146. doi:10.1007/s00453-008-9244-5. ISSN 0178-4617. Retrieved 9 April, 2013.
{{cite journal}}: Check date values in:|accessdate=(help)CS1 maint: multiple names: authors list (link) - ^ Corne, D., Knowles, J. (2003). "No free lunch and free leftovers theorems for multiobjective optimisation problems". Evolutionary Multi-Criterion Optimization. pp. 66–66. Retrieved 9 April, 2013.
{{cite book}}: Check date values in:|accessdate=(help); Unknown parameter|organization=ignored (help)CS1 maint: multiple names: authors list (link) - ^ Corne, D., Knowles, J. (2003). "Some multiobjective optimizers are better than others". Proceedings Congress Evolutionary Computation CEC '03. Vol. 4. pp. 2506–2512. doi:10.1109/CEC.2003.1299403.
{{cite book}}:|access-date=requires|url=(help); Check date values in:|accessdate=(help)CS1 maint: multiple names: authors list (link) - ^ Culberson, Joseph C. (1998). "On the futility of blind search: An algorithmic view of 'no free lunch'". Evolutionary Computation. 6 (2). MIT Press: 109–127. doi:10.1162/evco.1998.6.2.109. ISSN 1063-6560. Retrieved 9 April, 2013.
{{cite journal}}: Check date values in:|accessdate=(help); Unknown parameter|month=ignored (help) - ^ Giraud-Carrier, C., Provost, F. (2005). "Toward a Justification of Meta-learning: Is the No Free Lunch Theorem a Show-stopper?". Proceedings of the ICML-2005 Workshop on Meta-learning (PDF). pp. 12–19. Retrieved 9 April, 2013.
{{cite book}}: Check date values in:|accessdate=(help)CS1 maint: multiple names: authors list (link) - ^ Whitley, Darrell, Watson, Jean (2005), Burke, Edmund K. and Kendall, Graham (ed.), Complexity Theory and the No Free Lunch Theorem, Springer US, pp. 317–339, doi:10.1007/0-387-28356-0_11, ISBN 978-0-387-28356-2, retrieved 9 April, 2013
{{citation}}: Check date values in:|accessdate=(help)CS1 maint: multiple names: authors list (link) - ^ Mülhenbein, H.; Paaß, G. (1996). "From recombination of genes to the estimation of distribution I. Binary parameters". Lectures Notes in Computer Science: Parallel Problem Solving from Nature (PPSN IV). 1411: 178–187.
- ^ Hansen; Ostermeier (1996). "Adapting arbitrary normal mutation distributions in evolution strategies: The covariance matrix adaptation". Proceedings of the IEEE International Conference on Evolutionary Computation: 312–317.
- ^
Jastrebski, G.A. (2006). "Improving Evolution Strategies through Active Covariance Matrix Adaptation". 2006 IEEE World Congress on Computational Intelligence, Proceedings. IEEE. pp. 9719–9726. doi:10.1109/CEC.2006.1688662.
{{cite conference}}: Unknown parameter|booktitle=ignored (|book-title=suggested) (help); Unknown parameter|coauthors=ignored (|author=suggested) (help) - ^
Shir, Ofer M. (2006). Niche radius adaptation in the cma-es niching algorithm. Springer. pp. 142--151.
{{cite book}}: Unknown parameter|booktitle=ignored (help); Unknown parameter|coauthors=ignored (|author=suggested) (help) - ^
Storn, R. (1997). "Differential evolution - a simple and efficient heuristic for global optimization over continuous spaces". Journal of Global Optimization. 11 (4): 341–359. doi:10.1023/A:1008202821328.
{{cite journal}}: Unknown parameter|coauthors=ignored (|author=suggested) (help) - ^ Rubinstein, R.Y. (1997). "Optimization of Computer simulation Models with Rare Events". European Journal of Operations Research. 99 (1): 89–112. doi:10.1016/S0377-2217(96)00385-2.
- ^ Taillard, Eric; Voss, Stephan (1999). "POPMUSIC: Partial Optimization Metaheuristic Under Special Intensification Conditions" (PDF). Technical Report. Institute for Computer Sciences, heig-vd, Yverdon.
- ^ Geem, Z.W.; Kim, J.H.; Loganathan, G.V. (2001). "A new heuristic optimization algorithm: harmony search". Simulation. 76 (2): 60–68. doi:10.1177/003754970107600201.
- ^
Hanseth, O.; Aanestad, M. (2001). "Bootstrapping networks, communities and infrastructures. On the evolution of ICT solutions in heath care". First International Conference on Information Technology in Health Care (ITHC, September 6–7, 2001). Erasmus University, Rotterdam, The Netherlands.
{{cite conference}}: Unknown parameter|booktitle=ignored (|book-title=suggested) (help) - ^ Deb, K.; Pratap, A.; Agarwal, S.; Meyarivan, T. (2002). "A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II". IEEE Transactions on Evolutionary Computation. 6 (2): 182–197. doi:10.1109/4235.996017.
- ^ Kuk-Hyun Han and Jong-Hwan Kim, "Quantum-inspired evolutionary algorithm for a class of combinatorial optimization," in IEEE Transactions on Evolutionary Computation, vol. 6, no. 6, pp. 580-593, Dec. 2002, doi: 10.1109/TEVC.2002.804320.
- ^ Nakrani, S.; Tovey, S. (2004). "On honey bees and dynamic server allocation in Internet hosting centers". Adaptive Behavior. 12.
- ^ Krishnanand, K.; Ghose, D. (2009). "Glowworm swarm optimization for simultaneous capture of multiple local optima of multimodal functions". Swarm Intelligence. 3 (2): 87–124. doi:10.1007/s11721-008-0021-5.
- ^ Krishnanand, K.; Ghose, D. (2006). "Glowworm swarm based optimization algorithm for multimodal functions with collective robotics applications". Multiagent and Grid Systems. 2: 209–222.
- ^
Krishnanand, K.; Ghose, D. (2005). "Detection of multiple source locations using a glowworm metaphor with applications to collective robotics". Proceedings of IEEE Swarm Intelligence Symposium. pp. 84–91.
{{cite conference}}: Unknown parameter|booktitle=ignored (|book-title=suggested) (help) - ^ Karaboga, D. (2005). "An Idea Based On Honey Bee Swarm For Numerical Numerical Optimization". Technical Report-TR06. Erciyes University, Engineering Faculty, Computer Engineering Department.
- ^
Haddad, O. B.; Afshar, Abbas; Mariño, Miguel A.; et al. (2006). "Honey-bees mating optimization (HBMO) algorithm: a new heuristic approach for water resources optimization". Water Resources Management. 20 (5): 661–680. doi:10.1007/s11269-005-9001-3.
{{cite journal}}: Explicit use of et al. in:|first1=(help) - ^
Wierstra, D.; Schaul, T.; Peters, J.; Schmidhuber, J. (2008). "Natural Evolution Strategies" (PDF). Proceedings of the IEEE Congress on Evolutionary Computation (CEC). Hong Kong, China. pp. 3381–3387.
{{cite conference}}: Unknown parameter|booktitle=ignored (|book-title=suggested) (help) - ^ Yang, X.-S. (2008). Nature-Inspired Metaheuristic Algorithms. Luniver Press. ISBN 1-905986-28-9.
- ^
Husseinzadeh Kashan, A. (2009). "League Championship Algorithm: a new algorithm for numerical function optimization". Proceedings of IEEE International Conference of Soft Computing and Pattern Recognition (SoCPaR 2009). pp. 43–48.
{{cite conference}}: Unknown parameter|booktitle=ignored (|book-title=suggested) (help) - ^
Husseinzadeh Kashan, A. (2010). "A new algorithm for constrained optimization inspired by the sport league championships". Proceedings of IEEE World Congress on Computational Intelligence (WCCI 2010). pp. 487–494.
{{cite conference}}: Unknown parameter|booktitle=ignored (|book-title=suggested) (help) - ^ Husseinzadeh Kashan, A. (2011). "An Efficient Algorithm for Constrained Global Optimization and Application to Mechanical Engineering Design: League Championship Algorithm (LCA)". Computer Aided Design. 43 (12): 1769–1792. doi:10.1016/j.cad.2011.07.003.
- ^
Kadioglu, S.; Sellmann, M. (2009). "Dialectic Search". Proceedings of the International Conference on Principles and Practice of Constraint Programming (CP). Springer. pp. 486–500.
{{cite conference}}: Unknown parameter|booktitle=ignored (|book-title=suggested) (help) - ^ Yang, X.-S.; Deb, S. (2009). Cuckoo search via Lévy flights, in: World Congress on Nature & Biologically Inspired Computing (NaBIC 2009). IEEE Publication, USA. pp. 210–214.
- ^
Yang, X.-S. (2010). A New Metaheuristic Bat-Inspired Algorithm http://arxiv.org/abs/1004.4170, in: Nature Inspired Cooperative Strategies for Optimization (NISCO 2010) (Eds. J. R. Gonzalez et al.), Studies in Computational Intelligence,. Springer, Berlin. pp. 65–74.
{{cite book}}: External link in|title= - ^ Shah-Hosseini, Hamed (2011). "Principal components analysis by the galaxy-based search algorithm: a novel metaheuristic for continuous optimisation". International Journal of Computational Science and Engineering. 6 (1/2): 132–140. doi:10.1504/IJCSE.2011.041221.
- ^ Tamura, K.; Yasuda, K. (2011). "Primary Study of Spiral Dynamics Inspired Optimization". IEEJ Transactions on Electrical and Electronic Engineering. 6 (S1): S98–S100. doi:10.1002/tee.20628.
- ^ Tamura, K.; Yasuda, K. (2011). "Spiral Dynamics Inspired Optimization". Journal of Advanced Computational Intelligence and Intelligent Informatics. 15 (8): 1116–1122.
- ^ Civicioglu, P. (2012). "Transforming geocentric cartesian coordinates to geodetic coordinates by using differential search algorithm". Computers & Geosciences. 46: 229–247. doi:10.1016/j.cageo.2011.12.011.
- ^ Civicioglu,P. (2013). "Artificial Cooperative Search Algorithm for Numerical Optimization Problems". Information Sciences. 229: 58–76.
- ^
Tsai, Chun-Wei (2015). "Search Economics: A Solution Space and Computing Resource Aware Search Method". Proceedings of IEEE International Conference on Systems, Man and Cybernetics. pp. 2555–2560.
{{cite conference}}: Unknown parameter|booktitle=ignored (|book-title=suggested) (help) - ^ S. Kuo and Y. Chou, "Entanglement-Enhanced Quantum-Inspired Tabu Search Algorithm for Function Optimization," in IEEE Access, vol. 5, pp. 13236-13252, 2017, doi: 10.1109/ACCESS.2017.2723538.
- ^
Bouchekara H.R.E.H. (2017). "Most Valuable Player Algorithm: a novel optimization algorithm inspired from sport". Operational Research: 1–57. doi:https://doi.org/10.1007/s12351-017-0320-y.
{{cite journal}}: Check|doi=value (help); External link in|DOI= - ^ Y. Chou, S. Kuo, L. Yang and C. Yang, "Next Generation Metaheuristic: Jaguar Algorithm," in IEEE Access, vol. 6, pp. 9975-9990, 2018, doi: 10.1109/ACCESS.2018.2797059.