The Plant Propagation Algorithm (PPA) is a Nature-Inspired stochastic algorithm, which emulates the way plants, in particular the strawberry plant, propagate using runners. It has been experimentally tested both on unconstrained and constrained continuous global optimization problems and was found to be competitive against well established algorithms. This paper is concerned with its convergence analysis. It first puts forward a general convergence theorem for a large class of random algorithms, before the PPA convergence theorem is derived and proved. It then illustrates the results on simple problems.
Accepté le :
DOI : 10.1051/ro/2017037
Mots-clés : Strawberry algorithm, randomised algorithms, convergence analysis, global optimisation
@article{RO_2018__52_2_429_0, author = {Brahimi, Nassim and Salhi, Abdellah and Ourbih-Tari, Megdouda}, title = {Convergence analysis of the plant propagation algorithm for continuous global optimization}, journal = {RAIRO - Operations Research - Recherche Op\'erationnelle}, pages = {429--438}, publisher = {EDP-Sciences}, volume = {52}, number = {2}, year = {2018}, doi = {10.1051/ro/2017037}, zbl = {1401.90124}, mrnumber = {3880536}, language = {en}, url = {http://www.numdam.org/articles/10.1051/ro/2017037/} }
TY - JOUR AU - Brahimi, Nassim AU - Salhi, Abdellah AU - Ourbih-Tari, Megdouda TI - Convergence analysis of the plant propagation algorithm for continuous global optimization JO - RAIRO - Operations Research - Recherche Opérationnelle PY - 2018 SP - 429 EP - 438 VL - 52 IS - 2 PB - EDP-Sciences UR - http://www.numdam.org/articles/10.1051/ro/2017037/ DO - 10.1051/ro/2017037 LA - en ID - RO_2018__52_2_429_0 ER -
%0 Journal Article %A Brahimi, Nassim %A Salhi, Abdellah %A Ourbih-Tari, Megdouda %T Convergence analysis of the plant propagation algorithm for continuous global optimization %J RAIRO - Operations Research - Recherche Opérationnelle %D 2018 %P 429-438 %V 52 %N 2 %I EDP-Sciences %U http://www.numdam.org/articles/10.1051/ro/2017037/ %R 10.1051/ro/2017037 %G en %F RO_2018__52_2_429_0
Brahimi, Nassim; Salhi, Abdellah; Ourbih-Tari, Megdouda. Convergence analysis of the plant propagation algorithm for continuous global optimization. RAIRO - Operations Research - Recherche Opérationnelle, Tome 52 (2018) no. 2, pp. 429-438. doi : 10.1051/ro/2017037. http://www.numdam.org/articles/10.1051/ro/2017037/
[1] Simulated Annealing. In Local Search in Combinatorial Optimization. edited by and Wiley (1997) 91–120 | MR | Zbl
, and ,[2] Convergence of evolutionary algorithms on the n-dimensional continuous space. Cybernetics. IEEE Trans. 43 (2013) 1462–1472
, , , ,[3] A convergence proof for the particle swarm optimiser. Fundamenta Informaticae 105 (2010) 341–374 | DOI | MR | Zbl
and ,[4] Global convergence for evolution strategies in spherical problems: some simple proofs and difficulties. Theoretical Comput. Sci. 306 (2003) 269–289 | DOI | MR | Zbl
and ,[5] Drift Analysis of Ant Colony Optimization of Stochastic Linear Pseudo-Boolean Functions. Operat. Res. Lett. 45 (2017) 342–347 | DOI | MR | Zbl
, and ,[6] Clever Algorithms: Nature-Inspired Programming Recipes (2011)
,[7] Particle Swarm Optimization. In Vol. 93. John Wiley and Sons (2010)
,[8] A new algorithm inspired in the behavior of the social-spider for constrained optimization. Expert Syst. Appl. 41 (2014) 412–425 | DOI
and ,[9] A new optimizer using particle swarm theory. In Proc. of the 6th Inter. Sympos. Micro Machine and Human Scie. (MHS’95), IEEE, Nagoya, Japan (1995) 39–43 | DOI
, ,[10] Mixed variable structural optimization using Firefly Algorithm. Comput. Structures 89 (2011) 2325–2336 | DOI
, and ,[11] A graph-based ant system and its convergence. Future Generation Comput. Syst. 16 (2000) 873–888 | DOI
,[12] ACO algorithms with guaranteed convergence to the optimal solutions. Information Processing Lett. 82 (2002) 145–53 | DOI | MR | Zbl
,[13] Variable neighborhood search: Principles and applications. Eur. J. Operat. Res. 130 (2001) 449–467 | DOI | MR | Zbl
and ,[14] Adaptation in Natural and Artificial Systems, University of Michigan Press. Ann. Arbor, MI (1974) | MR | Zbl
,[15] An idea based on honey bee swarm for numerical optimization. Tech. Rep. (TR06), Erciyes University Press, Kayseri, Turkey (2005)
,[16] On the performance of artificial bee colony (ABC) algorithm. Appl. Soft Comput. J. 8 (2008) 687–697 | DOI
and ,[17] Swarm clustering based on flowers pollination by artificial bees. Studies Comput. Intell. 34 (2006) 191–202 | DOI
, , and ,[18] Optimization by Simulated Annealing. Science 220 (1983) 671–680 | DOI | MR | Zbl
, and ,[19] Equation of State Calculations by Fast Computing Machines. J. Chem. Phys. 21 (1953) 1087–1092 | DOI | Zbl
, , , and ,[20] Nature-inspired optimisation approaches and the new plant propagation algorithm. In Proc. of the International Conference on Numerical Analysis and Optimization ICeMATH ’11 (2011) K2-1–K2-8, Yogyakarta, Indonesia.
and ,[21] Experiences with stochastic algorithms for a class of constrained global optimisation problems. Recherche Opér. 34 (2000) 183–97 | Numdam | MR | Zbl
, , and ,[22] An estimation of distribution algorithm with guided mutation for a complex flow shop scheduling problem. In Proc. of 9th Ann. Genetic and Evolutionary Comput. Conf. (GECCO’07), edited by . ACM (2007) 570–576 | DOI
, and ,[23] A Novel Plant Propagation Algorithm: Modifications And Implementation. Science International-Lahore 28 (2015) 201–209
, , and , ,[24] A Seed-based Plant Propagation Algorithm: The feeding Station Model. Scientific World J. 2015 (2015) 1–16 | DOI
and ,[25] A plant propagation algorithm for constrained engineering optimisation problems. Math. Problems Eng. 2014 (2014) 1–10 | DOI
, , and ,[26] Convergence of the simulated annealing algorithm for continuous global optimization. J. Optimiz. Theory Appl. 104 (2000) 691–716 | DOI | MR | Zbl
,[27] Firefly algorithm, stochastic test functions and design optimisation. Inter. J. Bio-Inspired Comput. 2 (2010) 78–84 | DOI
,[28] Nature-Inspired Metaheuristic Algorithms. Luniver Press (2011)
,[29] Flower pollination algorithm for global optimization. In Unconventional Computation and Natural Computation. Springer (2012) 240–249 | DOI | Zbl
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