Evolutionary Computation Models

[1]  Frank Kursawe,et al.  A Variant of Evolution Strategies for Vector Optimization , 1990, PPSN.

[2]  Peter J. Angeline,et al.  Evolutionary Module Acquisition , 1993 .

[3]  D. Fogel The evolution of intelligent decision making in gaming , 1991 .

[4]  Hitoshi Iba,et al.  System Identification using Structured Genetic Algorithms , 1993, ICGA.

[5]  Anne L. Olsen Penalty functions and the knapsack problem , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[6]  Reinhard Lohmann,et al.  Application of Evolution Strategy in Parallel Populations , 1990, PPSN.

[7]  James Bailey,et al.  First we reshape our computers, then our computers reshape us: the broader intellectual impact of parallelism , 1993 .

[8]  Craig W. Reynolds Evolution of obstacle avoidance behavior: using noise to promote robust solutions , 1994 .

[9]  Lothar Thiele,et al.  A Mathematical Analysis of Tournament Selection , 1995, ICGA.

[10]  Nikolaus Hansen,et al.  Step-Size Adaption Based on Non-Local Use of Selection Information , 1994, PPSN.

[11]  Wolfgang Banzhaf,et al.  Interactive Evolution of Images , 1995, Evolutionary Programming.

[12]  David B. Fogel,et al.  A Comparison of Self-Adaptation Methods for Finite State Machines in Dynamic Environments , 1996, Evolutionary Programming.

[13]  Yuval Davidor,et al.  A Naturally Occurring Niche and Species Phenomenon: The Model and First Results , 1991, ICGA.

[14]  F. Sorbello,et al.  A genetic algorithm for the routing of VLSI circuits , 1991, Euro ASIC '91.

[15]  L. Darrell Whitley,et al.  Advanced Correlation Analysis of Operators for the Traveling Salesman Problem , 1994, PPSN.

[16]  Thomas Bäck,et al.  Extended Selection Mechanisms in Genetic Algorithms , 1991, ICGA.

[17]  David E. Goldberg,et al.  A niched Pareto genetic algorithm for multiobjective optimization , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[18]  Alice E. Smith,et al.  Genetic Optimization Using A Penalty Function , 1993, ICGA.

[19]  Craig Caldwell,et al.  Tracking a Criminal Suspect Through "Face-Space" with a Genetic Algorithm , 1991, International Conference on Genetic Algorithms.

[20]  Larry J. Eshelman,et al.  Crossover's Niche , 1993, ICGA.

[21]  Kenneth A. De Jong,et al.  On Decentralizing Selection Algorithms , 1995, ICGA.

[22]  Reinhard Männer,et al.  Towards an Optimal Mutation Probability for Genetic Algorithms , 1990, PPSN.

[23]  Nicholas J. Radcliffe,et al.  Genetic Set Recombination , 1992, FOGA.

[24]  W. Wcislo BEHAVIORAL ENVIRONMENTS AND EVOLUTIONARY CHANGE , 1989 .

[25]  Aharon Ben-Tal,et al.  Characterization of Pareto and Lexicographic Optimal Solutions , 1980 .

[26]  David R. Jefferson,et al.  Selection in Massively Parallel Genetic Algorithms , 1991, ICGA.

[27]  Kate Juliff,et al.  A Multi-chromosome Genetic Algorithm for Pallet Loading , 1993, International Conference on Genetic Algorithms.

[28]  Peter J. Fleming,et al.  Genetic Algorithms for Multiobjective Optimization: FormulationDiscussion and Generalization , 1993, ICGA.

[29]  Raj Seshu Binary decision trees and an “average-case” model for concept learning: implications for feature construction and the study of bias , 1994, COLT 1994.

[30]  Elliott Sober,et al.  From a biological point of view: The adaptive advantage of learning and a priori prejudice , 1994 .

[31]  Jens Lienig,et al.  A parallel genetic algorithm for two detailed routing problems , 1996, 1996 IEEE International Symposium on Circuits and Systems. Circuits and Systems Connecting the World. ISCAS 96.

[32]  Wolfgang Banzhaf,et al.  An expansion operator for interactive evolution , 1995, Proceedings of 1995 IEEE International Conference on Evolutionary Computation.

[33]  Kalyanmoy Deb,et al.  A Comparative Analysis of Selection Schemes Used in Genetic Algorithms , 1990, FOGA.

[34]  Michael M. Skolnick,et al.  Using Genetic Algorithms in Engineering Design Optimization with Non-Linear Constraints , 1993, ICGA.

[35]  Georges R. Harik,et al.  Finding Multimodal Solutions Using Restricted Tournament Selection , 1995, ICGA.

[36]  D. Fogel,et al.  A comparison of methods for self-adaptation in evolutionary algorithms. , 1995, Bio Systems.

[37]  David E. Goldberg,et al.  Alleles, loci and the traveling salesman problem , 1985 .

[38]  James E. Baker,et al.  Reducing Bias and Inefficienry in the Selection Algorithm , 1987, ICGA.

[39]  Yoshikazu Nishikawa,et al.  A Parallel Genetic Algorithm based on a Neighborhood Model and Its Application to Jobshop Scheduling , 1993, PPSN.

[40]  Michael J. Flynn,et al.  Very high-speed computing systems , 1966 .

[41]  Darrell Whitley,et al.  Genitor: a different genetic algorithm , 1988 .

[42]  Jim Smith,et al.  Self adaptation of mutation rates in a steady state genetic algorithm , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.

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

[44]  Nichael Lynn Cramer,et al.  A Representation for the Adaptive Generation of Simple Sequential Programs , 1985, ICGA.

[45]  Bruce E. Rosen,et al.  Genetic Algorithms and Very Fast Simulated Reannealing: A comparison , 1992 .

[46]  Dana S. Richards,et al.  Genetic Algorithms and Punctuated Equilibria in VLSI , 1990, PPSN.

[47]  John J. Grefenstette,et al.  Genetic Algorithms for Tracking Changing Environments , 1993, ICGA.

[48]  L. Darrell Whitley,et al.  Fundamental Principles of Deception in Genetic Search , 1990, FOGA.

[49]  John J. Grefenstette,et al.  Conditions for Implicit Parallelism , 1990, FOGA.

[50]  Ellie Baker,et al.  Evolving Line Drawings , 1993, ICGA.

[51]  Jin-Kao Hao,et al.  An empirical comparison of two evolutionary methods for satisfiability problems , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[52]  Raphael T. Haftka,et al.  Genetic Algorithms for Placing Actuators on Space Structures , 1993, International Conference on Genetic Algorithms.

[53]  Lawrence Davis,et al.  Training Feedforward Neural Networks Using Genetic Algorithms , 1989, IJCAI.

[54]  Andrew S. Grimshaw,et al.  Easy-to-use object-oriented parallel processing with Mentat , 1993, Computer.

[55]  J. W. Atmar,et al.  Comparing genetic operators with gaussian mutations in simulated evolutionary processes using linear systems , 1990, Biological Cybernetics.

[56]  Bernard Manderick,et al.  Fine-Grained Parallel Genetic Algorithms , 1989, ICGA.

[57]  Heinz Mühlenbein,et al.  Parallel Genetic Algorithms, Population Genetics, and Combinatorial Optimization , 1989, Parallelism, Learning, Evolution.

[58]  D. H. Kieronska,et al.  Genetic algorithms for network division problem , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[59]  Larry J. Eshelman,et al.  Biases in the Crossover Landscape , 1989, ICGA.

[60]  Kenneth E. Kinnear,et al.  Generality and Difficulty in Genetic Programming: Evolving a Sort , 1993, ICGA.

[61]  Günter Rudolph,et al.  Global Optimization by Means of Distributed Evolution Strategies , 1990, PPSN.

[62]  Patrick D. Surry,et al.  Fitness Variance of Formae and Performance Prediction , 1994, FOGA.

[63]  Thomas Bäck,et al.  Evolution Strategies for Mixed-Integer Optimization of Optical Multilayer Systems , 1995, Evolutionary Programming.

[64]  Michael C. Ferris,et al.  Genetic Algorithms for Combinatorial Optimization: The Assemble Line Balancing Problem , 1994, INFORMS J. Comput..

[65]  Terence C. Fogarty,et al.  Varying the Probability of Mutation in the Genetic Algorithm , 1989, ICGA.

[66]  A. Konagaya,et al.  Stochastic motif extraction using a genetic algorithm with the MDL principle , 1993, [1993] Proceedings of the Twenty-sixth Hawaii International Conference on System Sciences.

[67]  David B. Fogel,et al.  Meta-evolutionary programming , 1991, [1991] Conference Record of the Twenty-Fifth Asilomar Conference on Signals, Systems & Computers.

[68]  Lawrence Davis,et al.  Adapting Operator Probabilities in Genetic Algorithms , 1989, ICGA.

[69]  Jack Sklansky,et al.  Constrained Genetic Optimization via Dynarnic Reward-Penalty Balancing and Its Use in Pattern Recognition , 1989, ICGA.

[70]  James R. Levenick Inserting Introns Improves Genetic Algorithm Success Rate: Taking a Cue from Biology , 1991, ICGA.

[71]  Heinz Mühlenbein,et al.  Analysis of Selection, Mutation and Recombination in Genetic Algorithms , 1995, Evolution and Biocomputation.

[72]  Dirk Van Gucht,et al.  The effects of population size, heuristic crossover and local improvement on a genetic algorithm for the traveling salesman problem , 1989 .

[73]  Erik D. Goodman,et al.  Genetic Learning Procedures in Distributed Environments , 1987, ICGA.

[74]  Larry J. Eshelman,et al.  The CHC Adaptive Search Algorithm: How to Have Safe Search When Engaging in Nontraditional Genetic Recombination , 1990, FOGA.

[75]  Peter J. Angeline,et al.  Competitive Environments Evolve Better Solutions for Complex Tasks , 1993, ICGA.

[76]  J. David Schaffer,et al.  An Adaptive Crossover Distribution Mechanism for Genetic Algorithms , 1987, ICGA.

[77]  Thomas Bäck,et al.  Evolution Strategies on Noisy Functions: How to Improve Convergence Properties , 1994, PPSN.

[78]  Dana S. Richards,et al.  Punctuated Equilibria: A Parallel Genetic Algorithm , 1987, ICGA.

[79]  J. Holland Searching nonlinear functions for high values , 1989 .

[80]  Marc Schoenauer,et al.  Constrained GA Optimization , 1993, ICGA.

[81]  Bernd Freisleben,et al.  A genetic local search algorithm for solving symmetric and asymmetric traveling salesman problems , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.

[82]  Bernd Freisleben,et al.  New Genetic Local Search Operators for the Traveling Salesman Problem , 1996, PPSN.

[83]  Zbigniew Michalewicz,et al.  Using Cultural Algorithms for Constraint Handling in GENOCOP , 1995, Evolutionary Programming.

[84]  Shu-Yuen Hwang,et al.  A Genetic Algorithm with Disruptive Selection , 1993, ICGA.

[85]  Peter Ross,et al.  Cost Based Operator Rate Adaption: An Investigation , 1996, PPSN.

[86]  Nicholas J. Radcliffe,et al.  Forma Analysis and Random Respectful Recombination , 1991, ICGA.

[87]  Akihiko Konagaya,et al.  Learning Stochastic Motifs from Genetic Sequences , 1991, ML.

[88]  David E. Goldberg,et al.  Genetic Algorithms with Sharing for Multimodalfunction Optimization , 1987, ICGA.

[89]  Cheng-Yan Kao,et al.  A Genetic Algorithm Approach for Set Covering Problems , 1994, International Conference on Evolutionary Computation.

[90]  Takeshi Yoshimura,et al.  Efficient Algorithms for Channel Routing , 1982, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

[91]  David B. Fogel,et al.  On the Relationship between the Duration of an Encounter and the Evolution of Cooperation in the Iterated Prisoner's Dilemma , 1995, Evolutionary Computation.

[92]  Raphael T. Haftka,et al.  A Segregated Genetic Algorithm for Constrained Structural Optimization , 1995, ICGA.

[93]  Sam R. Thangiah,et al.  An Adaptive Clustering Method Using a Geometric Shape for Vehicle Routing Problems with Time Windows , 1995, ICGA.

[94]  Thomas Bäck,et al.  Optimal Mutation Rates in Genetic Search , 1993, ICGA.

[95]  Ephrahim Garcia,et al.  Evolutionary Optimization of a Neural Network- based Signal Processor for Photometric Data from an Automated DNA Sequencer , 1995, Evolutionary Programming.

[96]  Gordon Bell,et al.  C.mmp: a multi-mini-processor , 1972, AFIPS '72 (Fall, part II).

[97]  Donald R. Jones,et al.  Solving Partitioning Problems with Genetic Algorithms , 1991, International Conference on Genetic Algorithms.

[98]  Martina Gorges-Schleuter,et al.  Explicit Parallelism of Genetic Algorithms through Population Structures , 1990, PPSN.

[99]  Hitoshi Iba,et al.  Genetic programming using a minimum description length principle , 1994 .

[100]  David E. Goldberg,et al.  An Analysis of Reproduction and Crossover in a Binary-Coded Genetic Algorithm , 1987, ICGA.

[101]  L. Altenberg EMERGENT PHENOMENA IN GENETIC PROGRAMMING , 1994 .

[102]  D. Ackley A connectionist machine for genetic hillclimbing , 1987 .

[103]  Kazuhiko Kawamura,et al.  Exploring Problem-Specific Recombination Operators for Job Shop Scheduling , 1991, International Conference on Genetic Algorithms.

[104]  A. E. Eiben,et al.  Self-adaptivity for constraint satisfaction: learning penalty functions , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.

[105]  R. Anderson,et al.  Learning and evolution: a quantitative genetics approach. , 1995, Journal of theoretical biology.

[106]  David B. Fogel,et al.  Evolving Behaviors in the Iterated Prisoner's Dilemma , 1993, Evolutionary Computation.

[107]  Peter J. Angeline,et al.  The Effects of Noise on Self-Adaptive Evolutionary Optimization , 1996, Evolutionary Programming.

[108]  David B. Fogel,et al.  Evolving neurocontrollers using evolutionary programming , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[109]  Astro Teller,et al.  The evolution of mental models , 1994 .

[110]  L. Darrell Whitley,et al.  The GENITOR Algorithm and Selection Pressure: Why Rank-Based Allocation of Reproductive Trials is Best , 1989, ICGA.

[111]  David B. Fogel,et al.  CONTINUOUS EVOLUTIONARY PROGRAMMING: ANALYSIS AND EXPERIMENTS , 1995 .

[112]  Kalyanmoy Deb,et al.  A flexible optimization procedure for mechanical component design based on genetic adaptive search , 1998 .

[113]  Peter J. B. Hancock,et al.  An Empirical Comparison of Selection Methods in Evolutionary Algorithms , 1994, Evolutionary Computing, AISB Workshop.

[114]  David B. Fogel,et al.  An Evolutionary Programming Approach to Self-Adaptation on Finite State Machines , 1995, Evolutionary Programming.

[115]  Martina Gorges-Schleuter,et al.  ASPARAGOS An Asynchronous Parallel Genetic Optimization Strategy , 1989, ICGA.

[116]  L. Darrell Whitley,et al.  Modeling Simple Genetic Algorithms for Permutation Problems , 1994, FOGA.

[117]  L. Darrell Whitley,et al.  A Comparison of Genetic Sequencing Operators , 1991, ICGA.

[118]  William E. Hart,et al.  Optimizing an Arbitrary Function is Hard for the Genetic Algorithm , 1991 .

[119]  Christopher R. Houck,et al.  On the use of non-stationary penalty functions to solve nonlinear constrained optimization problems with GA's , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[120]  Hans Ros Some Results on Boolean Concept Learning by Genetic Algorithms , 1989, ICGA.

[121]  Gilbert Syswerda,et al.  A Study of Reproduction in Generational and Steady State Genetic Algorithms , 1990, FOGA.

[122]  Richard K. Belew,et al.  When Both Individuals and Populations Search: Adding Simple Learning to the Genetic Algorithm , 1989, ICGA.

[123]  Bernard Manderick,et al.  A Massively Parallel Genetic Algorithm: Implementation and First Analysis , 1991, ICGA.

[124]  Dirk Thierens,et al.  Elitist recombination: an integrated selection recombination GA , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[125]  Rajarshi Das,et al.  A Study of Control Parameters Affecting Online Performance of Genetic Algorithms for Function Optimization , 1989, ICGA.

[126]  Peter C. Cheeseman,et al.  Where the Really Hard Problems Are , 1991, IJCAI.

[127]  William M. Spears,et al.  Simple Subpopulation Schemes , 1998 .

[128]  David W. Coit,et al.  Adaptive Penalty Methods for Genetic Optimization of Constrained Combinatorial Problems , 1996, INFORMS J. Comput..

[129]  D. Fogel ASYMPTOTIC CONVERGENCE PROPERTIES OF GENETIC ALGORITHMS AND EVOLUTIONARY PROGRAMMING: ANALYSIS AND EXPERIMENTS , 1994 .

[130]  Takeshi Yamada,et al.  Optimal Population Size under Constant Computation Cost , 1994, PPSN.

[131]  A. E. Eiben,et al.  Genetic algorithms with multi-parent recombination , 1994, PPSN.

[132]  A. Ravindran,et al.  Engineering Optimization: Methods and Applications , 2006 .

[133]  Kalyanmoy Deb,et al.  An Investigation of Niche and Species Formation in Genetic Function Optimization , 1989, ICGA.

[134]  Gilbert Syswerda,et al.  Uniform Crossover in Genetic Algorithms , 1989, ICGA.

[135]  Patrick D. Surry,et al.  A Multi-objective Approach to Constrained Optimisation of Gas Supply Networks: the COMOGA Method , 1995, Evolutionary Computing, AISB Workshop.

[136]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .

[137]  Roger L. Wainwright,et al.  Multiple Vehicle Routing with Time and Capacity Constraints Using Genetic Algorithms , 1993, ICGA.

[138]  Z. Michalewicz,et al.  Genocop III: a co-evolutionary algorithm for numerical optimization problems with nonlinear constraints , 1995, Proceedings of 1995 IEEE International Conference on Evolutionary Computation.

[139]  Reiko Tanese,et al.  Parallel Genetic Algorithms for a Hypercube , 1987, ICGA.

[140]  Joseph L. Breeden,et al.  Optimizing Stochastic and Multiple Fitness Functions , 1995, Evolutionary Programming.

[141]  B. R. Fox,et al.  Genetic Operators for Sequencing Problems , 1990, FOGA.

[142]  Heinz Mühlenbein,et al.  Adaptation of population sizes by competing subpopulations , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.

[143]  D. J. Smith,et al.  A Study of Permutation Crossover Operators on the Traveling Salesman Problem , 1987, ICGA.

[144]  Jan Paredis,et al.  Co-evolutionary Constraint Satisfaction , 1994, PPSN.

[145]  Bruce Tidor,et al.  An Analysis of Selection Procedures with Particular Attention Paid to Proportional and Boltzmann Selection , 1993, International Conference on Genetic Algorithms.

[146]  W. Daniel Hillis,et al.  Co-evolving parasites improve simulated evolution as an optimization procedure , 1990 .

[147]  S. Ranjithan,et al.  Using genetic algorithms to solve a multiple objective groundwater pollution containment problem , 1994 .

[148]  H. Bremermann,et al.  AN EVOLUTION-TYPE SEARCH METHOD FOR CONVEX SETS. , 1964 .

[149]  C. G. Shaefer,et al.  The ARGOT Strategy: Adaptive Representation Genetic Optimizer Technique , 1987, ICGA.

[150]  Rostam Joobbani,et al.  Artificial Intelligence Approach to VLSI Routing , 1985 .

[151]  L. Darrell Whitley,et al.  Scheduling Problems and Traveling Salesmen: The Genetic Edge Recombination Operator , 1989, International Conference on Genetic Algorithms.

[152]  David E. Goldberg,et al.  Nonstationary Function Optimization Using Genetic Algorithms with Dominance and Diploidy , 1987, ICGA.

[153]  James Bowen,et al.  Solving Constraint Satisfaction Problems Using a Genetic/Systematic Search Hybrid That Realizes When to Quit , 1995, ICGA.

[154]  Charles C. Palmer,et al.  Representing trees in genetic algorithms , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[155]  Thomas Bäck,et al.  Evolutionary computation: an overview , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.

[156]  Bryant A. Julstrom,et al.  What Have You Done for Me Lately? Adapting Operator Probabilities in a Steady-State Genetic Algorithm , 1995, ICGA.

[157]  John J. Grefenstette,et al.  A Parallel Genetic Algorithm , 1987, ICGA.

[158]  William M. Spears,et al.  Adapting Crossover in Evolutionary Algorithms , 1995, Evolutionary Programming.

[159]  Thomas Bäck,et al.  Selective Pressure in Evolutionary Algorithms: A Characterization of Selection Mechanisms , 1994, International Conference on Evolutionary Computation.

[160]  Daniel L. Slotnick,et al.  The SOLOMON computer , 1962, AFIPS '62 (Fall).

[161]  Alden H. Wright,et al.  Genetic Algorithms for Real Parameter Optimization , 1990, FOGA.

[162]  David E. Goldberg,et al.  Genetic Algorithms, Tournament Selection, and the Effects of Noise , 1995, Complex Syst..

[163]  J. David Schaffer,et al.  Representation and Hidden Bias: Gray vs. Binary Coding for Genetic Algorithms , 1988, ML.

[164]  L. Darrell Whitley,et al.  Cellular Genetic Algorithms , 1993, ICGA.

[165]  James E. Baker,et al.  Adaptive Selection Methods for Genetic Algorithms , 1985, International Conference on Genetic Algorithms.

[166]  Thomas Bäck,et al.  An evolutionary heuristic for the maximum independent set problem , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[167]  L. C. Stayton,et al.  On the effectiveness of crossover in simulated evolutionary optimization. , 1994, Bio Systems.

[168]  Kenneth A. De Jong,et al.  Generation Gaps Revisited , 1992, FOGA.

[169]  Nicholas J. Radcliffe,et al.  The algebra of genetic algorithms , 1994, Annals of Mathematics and Artificial Intelligence.

[170]  David E. Goldberg,et al.  The Theory of Virtual Alphabets , 1990, PPSN.

[171]  Melanie Mitchell,et al.  Relative Building-Block Fitness and the Building Block Hypothesis , 1992, FOGA.

[172]  David Andre,et al.  Classifying protein segments as transmembrane domains using architecture-altering operations in genetic programming , 1996 .

[173]  John H. Holland,et al.  COGNITIVE SYSTEMS BASED ON ADAPTIVE ALGORITHMS1 , 1978 .

[174]  James C. Bean,et al.  Genetic Algorithms and Random Keys for Sequencing and Optimization , 1994, INFORMS J. Comput..

[175]  Erik D. Goodman,et al.  A Standard GA Approach to Native Protein Conformation Prediction , 1995 .

[176]  David E. Goldberg,et al.  A Genetic Algorithm for Parallel Simulated Annealing , 1992, PPSN.

[177]  Gunar E. Liepins,et al.  Some Guidelines for Genetic Algorithms with Penalty Functions , 1989, ICGA.

[178]  Heinz Mühlenbein,et al.  Predictive Models for the Breeder Genetic Algorithm I. Continuous Parameter Optimization , 1993, Evolutionary Computation.

[179]  Q. Tuan Pham,et al.  Competitive Evolution: A Natural Approach to Operator Selection , 1993, Evo Workshops.

[180]  J. Reed,et al.  Simulation of biological evolution and machine learning. I. Selection of self-reproducing numeric patterns by data processing machines, effects of hereditary control, mutation type and crossing. , 1967, Journal of theoretical biology.

[181]  Kok Cheong Wong,et al.  A New Diploid Scheme and Dominance Change Mechanism for Non-Stationary Function Optimization , 1995, ICGA.

[182]  H. Geiringer On the Probability Theory of Linkage in Mendelian Heredity , 1944 .

[183]  Jean-Michel Renders,et al.  Hybridizing genetic algorithms with hill-climbing methods for global optimization: two possible ways , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.

[184]  James C. Bean,et al.  A Genetic Algorithm for the Multiple-Choice Integer Program , 1997, Oper. Res..

[185]  L. Darrell Whitley,et al.  Lamarckian Evolution, The Baldwin Effect and Function Optimization , 1994, PPSN.

[186]  Takeshi Yamada,et al.  Conventional Genetic Algorithm for Job Shop Problems , 1991, ICGA.

[187]  Hideyuki Takagi,et al.  A Framework for Studying the Effects of Dynamic Crossover, Mutation, and Population Sizing in Genetic Algorithms , 1994, IEEE/Nagoya-University World Wisepersons Workshop.

[188]  Dirk Thierens,et al.  Mixing in Genetic Algorithms , 1993, ICGA.

[189]  Lawrence Davis,et al.  Applying Adaptive Algorithms to Epistatic Domains , 1985, IJCAI.

[190]  Zbigniew Michalewicz,et al.  GAVaPS-a genetic algorithm with varying population size , 1994, Proceedings of the First IEEE Conference on Evolutionary Computation. IEEE World Congress on Computational Intelligence.