A Seed-Based Plant Propagation Algorithm: The Feeding Station Model

The seasonal production of fruit and seeds is akin to opening a feeding station, such as a restaurant. Agents coming to feed on the fruit are like customers attending the restaurant; they arrive at a certain rate and get served at a certain rate following some appropriate processes. The same applies to birds and animals visiting and feeding on ripe fruit produced by plants such as the strawberry plant. This phenomenon underpins the seed dispersion of the plants. Modelling it as a queuing process results in a seed-based search/optimisation algorithm. This variant of the Plant Propagation Algorithm is described, analysed, tested on nontrivial problems, and compared with well established algorithms. The results are included.

[1]  Thomas Bäck,et al.  An Overview of Evolutionary Algorithms for Parameter Optimization , 1993, Evolutionary Computation.

[2]  L. W. Krefting,et al.  The Role of Some Birds and Mammals in Seed Germination , 1949 .

[3]  John A Lawrence,et al.  Applied Management Science , 2005 .

[4]  D. Levey,et al.  Directed seed dispersal by bellbirds in a tropical cloud forest. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[5]  D'arcy W. Thompson.  On Growth and Form , 1945 .

[6]  D. Karaboga,et al.  On the performance of artificial bee colony (ABC) algorithm , 2008, Appl. Soft Comput..

[7]  Robert B. Cooper,et al.  Introduction to Queueing Theory , 1973 .

[8]  M. Fenner.  Seeds: The Ecology of Regeneration in Plant Communities , 1992 .

[9]  Ling Wang,et al.  A hybrid particle swarm optimization with a feasibility-based rule for constrained optimization , 2007, Appl. Math. Comput..

[10]  Xin-She Yang,et al.  Firefly algorithm, stochastic test functions and design optimisation , 2010, Int. J. Bio Inspired Comput..

[11]  Abdellah Salhi,et al.  A Plant Propagation Algorithm for Constrained Engineering Optimisation Problems , 2014 .

[12]  Caro Lucas,et al.  Swarm Clustering Based on Flowers Pollination by Artificial Bees , 2006, Swarm Intelligence in Data Mining.

[13]  Wang Hong-Yuan,et al.  An Improved ISOMAP for Visualization and Classification of Multiple Manifolds , 2013, ICONIP 2013.

[14]  J. Golinski,et al.  An adaptive optimization system applied to machine synthesis , 1973 .

[15]  John D. C. Little,et al.  A PROOF FOR THE QUEUING FORMULA : , 2015 .

[16]  S. D. Hendrix.  Plant-Animal Interactions , 2015 .

[17]  S. Pimm,et al.  Dispersal of Amazonian birds in continuous and fragmented forest. , 2007, Ecology letters.

[18]  J. Tellería,et al.  Conservation of seed-dispersing migrant birds in Mediterranean habitats: Shedding light on patterns to preserve processes , 2005 .

[19]  S. Levin.  Population Dynamic Models in Heterogeneous Environments , 1976 .

[20]  C. Augspurger,et al.  Wind Dispersal of Artifical Fruits Varying in Mass, Area, and Morphology , 1987 .

[21]  E. Fraga,et al.  Nature-Inspired Optimisation Approaches and the New Plant Propagation Algorithm , 2011 .

[22]  Y. Fung,et al.  A Theory of Elasticity of the Lung , 1974 .

[23]  Erik Valdemar Cuevas Jiménez,et al.  A new algorithm inspired in the behavior of the social-spider for constrained optimization , 2014, Expert Syst. Appl..

[24]  S. A. H. Geritz,et al.  The efficacy of dispersal in relation to safe site area and seed production , 2004, Oecologia.

[25]  J. Little.  A Proof for the Queuing Formula: L = λW , 1961 .

[26]  Xin-She Yang,et al.  Flower Pollination Algorithm for Global Optimization , 2012, UCNC.

[27]  A. Gandomi,et al.  Mixed variable structural optimization using Firefly Algorithm , 2011 .

[28]  D. Janzen.  Herbivores and the Number of Tree Species in Tropical Forests , 1970, The American Naturalist.

[29]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[30]  Ashok Dhondu Belegundu,et al.  A Study of Mathematical Programming Methods for Structural Optimization , 1985 .

[31]  O. Pellmyr,et al.  Plant-animal interactions : an evolutionary approach , 2002 .

[32]  J D Littler,et al.  A PROOF OF THE QUEUING FORMULA , 1961 .

[33]  Jasbir S. Arora,et al.  Introduction to Optimum Design , 1988 .

[34]  H. J. D. Plessis,et al.  EFFICIENT GENETIC TRANSFORMATION OF STRAWBERRY (FRAGARIA X ANANASSA DUCH.) CULTIVAR SELEKTA , 1997 .

[35]  Hong-yuan Wang,et al.  An Improved ISOMAP for Visualization and Classification of Multiple Manifolds , 2013, ICONIP.

[36]  C. Herrera.  Seed dispersal by vertebrates , 2002 .

[37]  Alan Hastings,et al.  Dispersal strategies in patchy environments , 1984 .

[38]  P. Jordano.  Fruits and Frugivory , 2000 .

[39]  Xin Yao,et al.  Evolutionary programming made faster , 1999, IEEE Trans. Evol. Comput..

[40]  Jason Brownlee,et al.  Clever Algorithms: Nature-Inspired Programming Recipes , 2012 .

[41]  H. Dohlman.  Hormone signal response system , 1993, Nature.

[42]  Beverley J. Glover,et al.  Understanding flowers and flowering : an integrated approach , 2007 .

[43]  Dervis Karaboga,et al.  A modified Artificial Bee Colony (ABC) algorithm for constrained optimization problems , 2011, Appl. Soft Comput..

[44]  Xin-She Yang,et al.  Nature-Inspired Metaheuristic Algorithms , 2008 .

[45]  N. Stork,et al.  Extinction or 'co-extinction' rates? , 1993, Nature.

[46]  David B. Fogel,et al.  System Identification Through Simulated Evolution: A Machine Learning Approach to Modeling , 1991 .

[47]  Xin-She Yang,et al.  Multi-Objective Flower Algorithm for Optimization , 2014, ICCS.

[48]  Jing J. Liang,et al.  Problem Definitions and Evaluation Criteria for the CEC 2005 Special Session on Real-Parameter Optimization , 2005 .

[49]  Dervis Karaboga,et al.  AN IDEA BASED ON HONEY BEE SWARM FOR NUMERICAL OPTIMIZATION , 2005 .

[50]  A. Reynolds,et al.  Free-Flight Odor Tracking in Drosophila Is Consistent with an Optimal Intermittent Scale-Free Search , 2007, PloS one.

[51]  Robert B. Cooper,et al.  An Introduction To Queueing Theory , 2016 .

[52]  Carlos A. Coello Coello,et al.  Solving Engineering Optimization Problems with the Simple Constrained Particle Swarm Optimizer , 2008, Informatica.

[53]  Jing J. Liang,et al.  Problem Deflnitions and Evaluation Criteria for the CEC 2006 Special Session on Constrained Real-Parameter Optimization , 2006 .

[54]  Russell C. Eberhart,et al.  A new optimizer using particle swarm theory , 1995, MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science.

[55]  Xin-She Yang,et al.  Engineering optimisation by cuckoo search , 2010, Int. J. Math. Model. Numer. Optimisation.

[56]  P. Isenmann,et al.  Bird-dispersed seed rain and seedling establishment in patchy Mediterranean vegetation , 1994 .

[57]  Mesut Gündüz,et al.  A recombination-based hybridization of particle swarm optimization and artificial bee colony algorithm for continuous optimization problems , 2013, Appl. Soft Comput..