On Analysis and Performance Improvement of Evolutionary Algorithms Based on its Complex Network Structure - A Summary Overview

In this participation there is sketched and explained mutual intersection between complex networks and evolutionary computation including summarization of our previous results. It is sketched how dynamics of evolutionary algorithm can be converted into a complex network and based on its properties like degree centrality etc. can be improved performance of used evolutionary algorithm. Results presented here are currently numerical demonstration rather than theoretical mathematical proofs. Paper discusses results from differential evolution, self-organizing migrating algorithm, genetic algorithms and artificial bee colony. We open question whether evolutionary algorithms really create complex network structures and whether this knowledge can be successfully used like feedback for control of evolutionary dynamics and its improvement in order to increase the performance of evolutionary algorithms.

[1]  Magdalena Metlicka,et al.  Chaos-driven Discrete Artificial Bee Colony , 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

[2]  Xin-She Yang,et al.  Cuckoo Search via Lévy flights , 2009, 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC).

[3]  Kenneth V. Price,et al.  An introduction to differential evolution , 1999 .

[4]  Magdalena Metlicka,et al.  Ensemble centralities based adaptive Artificial Bee algorithm , 2015, 2015 IEEE Congress on Evolutionary Computation (CEC).

[5]  Xin-She Yang,et al.  Firefly Algorithms for Multimodal Optimization , 2009, SAGA.

[6]  Michal Pluhacek,et al.  Complex network analysis of differential evolution algorithm applied to flowshop with no-wait problem , 2014, 2014 IEEE Symposium on Differential Evolution (SDE).

[7]  Ivan Zelinka,et al.  Self-Organizing Migrating Algorithm , 2016 .

[8]  S. N. Dorogovtsev,et al.  Evolution of networks , 2001, cond-mat/0106144.

[9]  William E. Hart,et al.  Recent Advances in Memetic Algorithms , 2008 .

[10]  Michal Pluhacek,et al.  PSO as Complex Network - Capturing the Inner Dynamics - Initial Study , 2015, AECIA.

[11]  H. P. Schwefel,et al.  Numerische Optimierung von Computermodellen mittels der Evo-lutionsstrategie , 1977 .

[12]  V. Latora,et al.  Complex networks: Structure and dynamics , 2006 .

[13]  David B. Fogel,et al.  Unearthing a Fossil from the History of Evolutionary Computation , 1998, Fundam. Informaticae.

[14]  Roman Senkerik,et al.  Preliminary investigation on relations between complex networks and evolutionary algorithms dynamics , 2010, 2010 International Conference on Computer Information Systems and Industrial Management Applications (CISIM).

[15]  Ingo Rechenberg,et al.  Evolutionsstrategie : Optimierung technischer Systeme nach Prinzipien der biologischen Evolution , 1973 .

[16]  Lenka Skanderova,et al.  Differential Evolution Dynamic Analysis in the Form of Complex Networks , 2016 .

[17]  Alessandro Vespignani,et al.  Dynamical Processes on Complex Networks , 2008 .

[18]  Roman Senkerik,et al.  Do Evolutionary Algorithm Dynamics Create Complex Network Structures? , 2011, Complex Syst..

[19]  Sean P. Meyn.  Control Techniques for Complex Networks: Workload , 2007 .

[20]  Xin-She Yang,et al.  A New Metaheuristic Bat-Inspired Algorithm , 2010, NICSO.

[21]  Jörn Schönberger.  Operational Freight Carrier Planning: Basic Concepts, Optimization Models and Advanced Memetic Algorithms , 2005 .

[22]  Kay Chen Tan,et al.  Multi-Objective Memetic Algorithms , 2009 .

[23]  Michal Pluhacek,et al.  Evolutionary algorithms dynamics and its hidden complex network structures , 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

[24]  Xiang Li,et al.  Fundamentals of Complex Networks: Models, Structures and Dynamics , 2015 .

[25]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[26]  Heinz G. Schuster,et al.  Handbook of Chaos Control: SCHUSTER:HDBK.CHAOS CONTR O-BK , 1999 .

[27]  Godfrey C. Onwubolu,et al.  New optimization techniques in engineering , 2004, Studies in Fuzziness and Soft Computing.

[28]  Eckehard Schöll,et al.  Handbook of Chaos Control , 2007 .

[29]  Thomas Stützle,et al.  Ant Colony Optimization , 2009, EMO.

[30]  Ivan Zelinka.  IWCFTA2012 Keynote Speech III - On Close Relations of Evolutionary Dynamics, Chaos and Complexity , 2012 .

[31]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[32]  Ivan Zelinka,et al.  On Mutual Relations amongst Evolutionary Algorithm Dynamics and Its Hidden Complex Network Structures: An Overview and Recent Advances , 2017 .

[33]  Michal Pluhacek,et al.  Hidden Complexity of Evolutionary Dynamics: Analysis , 2014 .