A survey of evolutionary algorithms using metameric representations

Evolutionary algorithms have been used to solve a number of variable-length problems, many of which share a common representation. A set of design variables is repeatedly defined, giving the genome a segmented structure. Each segment encodes a portion, frequently a single component, of the solution. For example, in a wind farm design problem each segment may encode the position and height of a single turbine. This is described as a metameric representation, with each segment referred to as a metavariable. The number of metavariables can vary among solutions, requiring modifications to the traditional fixed-length evolutionary operators. This paper surveys the literature that uses metameric representations with a focus on the problems being solved, the specifics of the representation, and the modifications to evolutionary operators. While there is little cross-referencing among the cited articles, it is demonstrated that there is already a strong overlap in their methodologies. By considering problems using a metameric representation as a single class, greater recognition of commonalities and differences among these works can be achieved. This could allow for the development of more efficient metameric evolutionary algorithms.

[1]  Woo Suck Han,et al.  Improved genetic algorithm for multidisciplinary optimization of composite laminates , 2008 .

[2]  K. Lakshmi,et al.  Multi-objective optimal design of laminated composite skirt using hybrid NSGA , 2013 .

[3]  Lifeng Xi,et al.  Evolving artificial neural networks using an improved PSO and DPSO , 2008, Neurocomputing.

[4]  Andries Petrus Engelbrecht,et al.  Dynamic clustering using particle swarm optimization with application in image segmentation , 2006, Pattern Analysis and Applications.

[5]  Marc Schoenauer,et al.  Shape Representations and Evolution Schemes , 1996, Evolutionary Programming.

[6]  Julian Francis Miller Cartesian Genetic Programming , 2011, Cartesian Genetic Programming.

[7]  Xin Yao,et al.  Evolving artificial neural networks , 1999, Proc. IEEE.

[8]  Gul Muhammad Khan,et al.  Fast learning neural networks using Cartesian genetic programming , 2013, Neurocomputing.

[9]  Olivier L. de Weck,et al.  Multi-objective genetic algorithm for the automated planning of a wireless sensor network to monitor a critical facility , 2004, SPIE Defense + Commercial Sensing.

[10]  Alex Alves Freitas,et al.  A Survey of Evolutionary Algorithms for Clustering , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[11]  Kenneth A. De Jong,et al.  Using genetic algorithms for concept learning , 1993, Machine Learning.

[12]  Franz Rothlauf,et al.  Representations for genetic and evolutionary algorithms , 2002, Studies in Fuzziness and Soft Computing.

[13]  Layne T. Watson,et al.  COMPOSITE LAMINATE DESIGN OPTIMIZATION BY GENETIC ALGORITHM WITH GENERALIZED ELITIST SELECTION , 2001 .

[14]  C.-Y. Lee,et al.  Variable Length Genomes for Evolutionary Algorithms , 2000, GECCO.

[15]  Hitoshi Iba,et al.  Evolving analog circuits by variable length chromosomes , 2003 .

[16]  Han Kyu Park,et al.  Genetic approach with a new representation for base station placement in mobile communications , 2001, IEEE 54th Vehicular Technology Conference. VTC Fall 2001. Proceedings (Cat. No.01CH37211).

[17]  Elliot Meyerson,et al.  Evolving Deep Neural Networks , 2017, Artificial Intelligence in the Age of Neural Networks and Brain Computing.

[18]  Kenneth O. Stanley,et al.  Compositional Pattern Producing Networks : A Novel Abstraction of Development , 2007 .

[19]  L. Darrell Whitley,et al.  Genetic algorithms and neural networks: optimizing connections and connectivity , 1990, Parallel Comput..

[20]  Damiano Pasini,et al.  Optimum stacking sequence design of composite materials Part II: Variable stiffness design , 2010 .

[21]  Kim-Fung Man,et al.  A Jumping-Genes Paradigm for Optimizing Factory WLAN Network , 2007, IEEE Transactions on Industrial Informatics.

[22]  M. Y. Hussaini,et al.  Placement of wind turbines using genetic algorithms , 2005 .

[23]  Leon Poladian A genotype-to-phenotype mapping for microstructured polymer optical fibres , 2011, 2011 IEEE Congress of Evolutionary Computation (CEC).

[24]  Alireza Emami,et al.  New approach on optimization in placement of wind turbines within wind farm by genetic algorithms , 2010 .

[25]  Hak-Keung Lam,et al.  Tuning of the structure and parameters of a neural network using an improved genetic algorithm , 2003, IEEE Trans. Neural Networks.

[26]  Qing Song,et al.  Wind farm layout optimization using genetic algorithm with different hub height wind turbines , 2013 .

[27]  Subramaniam Rajan,et al.  Sizing, Shape, and Topology Design Optimization of Trusses Using Genetic Algorithm , 1995 .

[28]  Mathias Giger Representation concepts in evolutionary algorithm-based structural optimization , 2007 .

[29]  Marc Schoenauer,et al.  Mechanical inclusions identification by evolutionary computation , 1996 .

[30]  Anil K. Jain,et al.  Data clustering: a review , 1999, CSUR.

[31]  Murat Tunc,et al.  Optimal positioning of wind turbines on Gökçeada using multi‐objective genetic algorithm , 2010 .

[32]  Shiro Usui,et al.  Mutation-based genetic neural network , 2005, IEEE Transactions on Neural Networks.

[33]  Enrique Alba,et al.  Optimal Sensor Network Layout Using Multi-Objective Metaheuristics , 2008, J. Univers. Comput. Sci..

[34]  W. Banzhaf Artificial Regulatory Networks and Genetic Programming , 2003 .

[35]  Dorothea Heiss-Czedik,et al.  An Introduction to Genetic Algorithms. , 1997, Artificial Life.

[36]  Jaume Bacardit,et al.  Bloat Control and Generalization Pressure Using the Minimum Description Length Principle for a Pittsburgh Approach Learning Classifier System , 2005, IWLCS.

[37]  Tomasz Arciszewski,et al.  Evolutionary computation and structural design: A survey of the state-of-the-art , 2005 .

[38]  Mengjie Zhang,et al.  Evolving Deep Convolutional Neural Networks for Image Classification , 2017, IEEE Transactions on Evolutionary Computation.

[39]  Jordan B. Pollack,et al.  Gene Regulatory Network Evolution Through Augmenting Topologies , 2015, IEEE Transactions on Evolutionary Computation.

[40]  Kalyanmoy Deb,et al.  Simultaneous topology, shape and size optimization of truss structures by fully stressed design based on evolution strategy , 2015 .

[41]  Lin-Yu Tseng,et al.  A genetic approach to the automatic clustering problem , 2001, Pattern Recognit..

[42]  Manuel Burgos Payán,et al.  Optimization of Wind Farm Turbine Layout Including Decision Making Under Risk , 2012, IEEE Systems Journal.

[43]  Ganapati Panda,et al.  A survey on nature inspired metaheuristic algorithms for partitional clustering , 2014, Swarm Evol. Comput..

[44]  Roy George,et al.  A variable-length genetic algorithm for clustering and classification , 1995, Pattern Recognit. Lett..

[45]  Vittorio Maniezzo,et al.  Genetic evolution of the topology and weight distribution of neural networks , 1994, IEEE Trans. Neural Networks.

[46]  Geoffrey A. Hollinger,et al.  Evolutionary design of fault-tolerant analog control for a piezoelectric pipe-crawling robot , 2006, GECCO '06.

[47]  Alistair Munro,et al.  Evolving fuzzy rule based controllers using genetic algorithms , 1996, Fuzzy Sets Syst..

[48]  Peter Widmayer,et al.  Evolutionary multiobjective optimization for base station transmitter placement with frequency assignment , 2003, IEEE Trans. Evol. Comput..

[49]  Yingwu Chen,et al.  Reconfiguration of satellite orbit for cooperative observation using variable-size multi-objective differential evolution , 2015, Eur. J. Oper. Res..

[50]  Martin Trefzer,et al.  On the Advantages of Variable Length GRNs for the Evolution of Multicellular Developmental Systems , 2013, IEEE Transactions on Evolutionary Computation.

[51]  Mandar A. Chitre,et al.  Direct Policy Search with Variable-Length Genetic Algorithm for Single Beacon Cooperative Path Planning , 2012, DARS.

[52]  Emmanuel Awa,et al.  On learning to generate wind farm layouts , 2013, GECCO '13.

[53]  Patrick D. Surry,et al.  Formal Algorithms + Formal Representations = Search Strategies , 1996, PPSN.

[54]  Ossama Abdelkhalik,et al.  Hidden Genes Genetic Algorithm for Multi-Gravity-Assist Trajectories Optimization , 2011 .

[55]  Francisco Luna,et al.  Evolutionary algorithms for solving the automatic cell planning problem: a survey , 2010 .

[56]  A. Rama Mohan Rao,et al.  Discrete hybrid PSO algorithm for design of laminate composites with multiple objectives , 2011 .

[57]  L. Buydens,et al.  Hybrid genetic algorithm-tabu search approach for optimising multilayer optical coatings , 2003 .

[58]  Erik K. Antonsson,et al.  Efficient automatic engineering design synthesis via evolutionary exploration , 2002 .

[59]  Krystel K. Castillo-Villar,et al.  A Review of Methodological Approaches for the Design and Optimization of Wind Farms , 2014 .

[60]  Manuel Burgos Payán,et al.  An evolutive algorithm for wind farm optimal design , 2007, Neurocomputing.

[61]  William F. Punch,et al.  Crossover gene selection by spatial location , 2006, GECCO '06.

[62]  Ujjwal Maulik,et al.  Genetic clustering for automatic evolution of clusters and application to image classification , 2002, Pattern Recognit..

[63]  Antonio J. Nebro,et al.  A survey of multi-objective metaheuristics applied to structural optimization , 2014 .

[64]  Kalyanmoy Deb,et al.  Solving metameric variable-length optimization problems using genetic algorithms , 2017, Genetic Programming and Evolvable Machines.

[65]  Marco Montemurro,et al.  A Two-Level Procedure for the Global Optimum Design of Composite Modular Structures—Application to the Design of an Aircraft Wing , 2012, J. Optim. Theory Appl..

[66]  Carlo Poloni,et al.  Optimization of wind turbine positioning in large windfarms by means of a genetic algorithm , 1994 .

[67]  J. B. Grimbleby,et al.  Automatic analogue circuit synthesis using genetic algorithms , 2000 .

[68]  Marley M. B. R. Vellasco,et al.  Variable Length Representation in Evolutionary Electronics , 2000, Evolutionary Computation.

[69]  Jian Chen,et al.  Multi-objective optimization for coverage control in wireless sensor network with adjustable sensing radius , 2009, Comput. Math. Appl..

[70]  S. Bandyopadhyay,et al.  Nonparametric genetic clustering: comparison of validity indices , 2001, IEEE Trans. Syst. Man Cybern. Syst..

[71]  Franz Rothlauf,et al.  Design of Modern Heuristics: Principles and Application , 2011 .

[72]  Jain-Shing Wu,et al.  Wireless Heterogeneous Transmitter Placement Using Multiobjective Variable-Length Genetic Algorithm , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[73]  Isaac M Daniel,et al.  Engineering Mechanics of Composite Materials , 1994 .

[74]  Abdullah Al Mamun,et al.  A memetic evolutionary search algorithm with variable length chromosome for rule extraction , 2008, 2008 IEEE International Conference on Systems, Man and Cybernetics.

[75]  Riccardo Poli,et al.  A Field Guide to Genetic Programming , 2008 .

[76]  Konstantinos P. Ferentinos,et al.  Adaptive design optimization of wireless sensor networks using genetic algorithms , 2007, Comput. Networks.

[77]  Marco Montemurro,et al.  A Two-Level Procedure for the Global Optimum Design of Composite Modular Structures—Application to the Design of an Aircraft Wing , 2012, J. Optim. Theory Appl..

[78]  P. Bentley,et al.  Evolving beyond perfection: an investigation of the effects of long-term evolution on fractal gene regulatory networks. , 2004, Bio Systems.

[79]  Wolfgang Banzhaf,et al.  A comparison of linear genetic programming and neural networks in medical data mining , 2001, IEEE Trans. Evol. Comput..

[80]  R. Haftka,et al.  Improved genetic algorithm for minimum thickness composite laminate design , 1995 .

[81]  Beatriz Souza Leite Pires de Lima,et al.  Optimal design of submarine pipeline routes by genetic algorithm with different constraint handling techniques , 2014, Adv. Eng. Softw..

[82]  Alex A. Freitas,et al.  Discovering comprehensible classification rules with a genetic algorithm , 2000, Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512).

[83]  Kuo-Sheng Cheng,et al.  Evolution-Based Tabu Search Approach to Automatic Clustering , 2007, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[84]  Sanghamitra Bandyopadhyay,et al.  VGA-Classifier: design and applications , 2000, IEEE Trans. Syst. Man Cybern. Part B.

[85]  Nima Jafari Navimipour,et al.  Deployment strategies in the wireless sensor network: A comprehensive review , 2016, Comput. Commun..

[86]  Paolo Ermanni,et al.  Evolutionary truss topology optimization using a graph-based parameterization concept , 2006 .

[87]  Dario Floreano,et al.  Neuroevolution: from architectures to learning , 2008, Evol. Intell..

[88]  Xin Yao,et al.  A new evolutionary system for evolving artificial neural networks , 1997, IEEE Trans. Neural Networks.

[89]  S. Vel,et al.  MULTI-OBJECTIVE OPTIMIZATION OF FIBER REINFORCED COMPOSITE LAMINATES FOR STRENGTH, STIFFNESS AND MINIMAL MASS , 2006 .

[90]  K. Deb,et al.  Design of truss-structures for minimum weight using genetic algorithms , 2001 .

[91]  David Keller,et al.  Global laminate optimization on geometrically partitioned shell structures , 2011 .

[92]  Hannu Koivisto,et al.  Fuzzy classifier identification using decision tree and multiobjective evolutionary algorithms , 2008, Int. J. Approx. Reason..

[93]  Damiano Pasini,et al.  Optimum stacking sequence design of composite materials Part I: Constant stiffness design , 2009 .

[94]  Julian Francis Miller,et al.  Redundancy and computational efficiency in Cartesian genetic programming , 2006, IEEE Transactions on Evolutionary Computation.

[95]  A. Spirov,et al.  Using evolutionary computations to understand the design and evolution of gene and cell regulatory networks. , 2013, Methods.

[96]  Christian Igel,et al.  Evolutionary Optimization of Neural Systems: The Use of Strategy Adaptation , 2005 .

[97]  Franz Rothlauf,et al.  Design of Modern Heuristics , 2011, Natural Computing Series.

[98]  Julian Francis Miller,et al.  Principles in the Evolutionary Design of Digital Circuits—Part II , 2000, Genetic Programming and Evolvable Machines.

[99]  Kenneth O. Stanley,et al.  A Hypercube-Based Encoding for Evolving Large-Scale Neural Networks , 2009, Artificial Life.

[100]  Francisco Herrera,et al.  Genetics-Based Machine Learning for Rule Induction: State of the Art, Taxonomy, and Comparative Study , 2010, IEEE Transactions on Evolutionary Computation.

[101]  Kenneth A. De Jong,et al.  Evolving Behaviors for Cooperating Agents , 2000, ISMIS.

[102]  Alina Sîrbu,et al.  Comparison of evolutionary algorithms in gene regulatory network model inference , 2010, BMC Bioinformatics.

[103]  W. Langdon The evolution of size in variable length representations , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[104]  Shafiqur Rehman,et al.  Iterative non-deterministic algorithms in on-shore wind farm design: A brief survey , 2013 .

[105]  Wolfgang Banzhaf,et al.  Genetic Programming: An Introduction , 1997 .

[106]  Chung-Fu Chang,et al.  Optimising train movements through coast control using genetic algorithms , 1997 .

[107]  Hitoshi Iba,et al.  An Effective Method for Evolving Reaction Networks in Synthetic Biochemical Systems , 2015, IEEE Transactions on Evolutionary Computation.

[108]  Ranga Vemuri,et al.  An Automated Passive Analog Circuit Synthesis Framework using Genetic Algorithms , 2007, IEEE Computer Society Annual Symposium on VLSI (ISVLSI '07).

[109]  Annie S. Wu,et al.  Evolving control for distributed micro air vehicles , 1999, Proceedings 1999 IEEE International Symposium on Computational Intelligence in Robotics and Automation. CIRA'99 (Cat. No.99EX375).

[110]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[111]  Javier Serrano González,et al.  A review and recent developments in the optimal wind-turbine micro-siting problem , 2014 .

[112]  Lajos Hanzo,et al.  A Survey of Multi-Objective Optimization in Wireless Sensor Networks: Metrics, Algorithms, and Open Problems , 2016, IEEE Communications Surveys & Tutorials.

[113]  Leon Poladian,et al.  Evolutionary design of single-mode microstructured polymer optical fibres using an artificial embryogeny representation , 2007, GECCO '07.

[114]  Michèle Sebag,et al.  Compact Unstructured Representations for Evolutionary Design , 2002, Applied Intelligence.

[115]  Jason D. Lohn,et al.  A circuit representation technique for automated circuit design , 1999, IEEE Trans. Evol. Comput..

[116]  Armando Miguel Awruch,et al.  Design optimization of composite laminated structures using genetic algorithms and finite element analysis , 2009 .

[117]  Isamu Kajitani,et al.  Variable length chromosome GA for evolvable hardware , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.

[118]  D. Fogel,et al.  Discovering patterns in spatial data using evolutionary programming , 1996 .

[119]  Philippe Bouillard,et al.  Multiobjective topology optimization of truss structures with kinematic stability repair , 2012 .

[120]  Sung-Bae Cho,et al.  Automated synthesis of multiple analog circuits using evolutionary computation for redundancy-based fault-tolerance , 2012, Appl. Soft Comput..

[121]  Swagatam Das,et al.  Kernel-induced fuzzy clustering of image pixels with an improved differential evolution algorithm , 2010, Inf. Sci..

[122]  Julian Francis Miller,et al.  Cartesian genetic programming , 2010, GECCO.

[123]  Yao Zhao,et al.  A genetic clustering algorithm using a message-based similarity measure , 2012, Expert Syst. Appl..

[124]  Tatiana Kalganova,et al.  Open-ended evolution to discover analogue circuits for beyond conventional applications , 2012, Genetic Programming and Evolvable Machines.

[125]  Risto Miikkulainen,et al.  Evolving Neural Networks through Augmenting Topologies , 2002, Evolutionary Computation.

[126]  P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .

[127]  Michael Hecker,et al.  Gene regulatory network inference: Data integration in dynamic models - A review , 2009, Biosyst..

[128]  Sylvain Cussat-Blanc,et al.  Gene regulated car driving: using a gene regulatory network to drive a virtual car , 2014, Genetic Programming and Evolvable Machines.