Cultured differential evolution for constrained optimization

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

[2]  M. Papadrakakis,et al.  Multi-objective design optimization using cascade evolutionary computations , 2005 .

[3]  C. Papadimitriou.  Pareto optimal sensor locations for structural identification , 2005 .

[4]  Yaochu Jin,et al.  Knowledge incorporation in evolutionary computation , 2005 .

[5]  G. Winter,et al.  Single and multiobjective frame optimization by evolutionary algorithms and the auto-adaptive rebirth operator , 2004 .

[6]  Carlos A. Coello Coello,et al.  An Improved Diversity Mechanism for Solving Constrained Optimization Problems Using a Multimembered Evolution Strategy , 2004, GECCO.

[7]  Ricardo Landa Becerra,et al.  Efficient evolutionary optimization through the use of a cultural algorithm , 2004 .

[8]  Ivan Zelinka,et al.  MIXED INTEGER-DISCRETE-CONTINUOUS OPTIMIZATION BY DIFFERENTIAL EVOLUTION Part 1: the optimization method , 2004 .

[9]  Kaisa Miettinen,et al.  Numerical Comparison of Some Penalty-Based Constraint Handling Techniques in Genetic Algorithms , 2003, J. Glob. Optim..

[10]  Robert G. Reynolds,et al.  Cultural swarms: modeling the impact of culture on social interaction and problem solving , 2003, Proceedings of the 2003 IEEE Swarm Intelligence Symposium. SIS'03 (Cat. No.03EX706).

[11]  A. E. Eiben,et al.  Introduction to Evolutionary Computing , 2003, Natural Computing Series.

[12]  Carlos A. Coello Coello,et al.  Adding Knowledge And Efficient Data Structures To Evolutionary Programming: A Cultural Algorithm For Constrained Optimization , 2002, GECCO.

[13]  Gary B. Lamont,et al.  Evolutionary Algorithms for Solving Multi-Objective Problems , 2002, Genetic Algorithms and Evolutionary Computation.

[14]  Marc Schoenauer,et al.  ASCHEA: new results using adaptive segregational constraint handling , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[15]  Feng-Sheng Wang,et al.  Hybrid differential evolution with multiplier updating method for nonlinear constrained optimization problems , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[16]  J. Lampinen.  A constraint handling approach for the differential evolution algorithm , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[17]  Carlos A. Coello Coello,et al.  THEORETICAL AND NUMERICAL CONSTRAINT-HANDLING TECHNIQUES USED WITH EVOLUTIONARY ALGORITHMS: A SURVEY OF THE STATE OF THE ART , 2002 .

[18]  Ian C. Parmee,et al.  Evolutionary and adaptive computing in engineering design , 2001 .

[19]  Robert G. Reynolds,et al.  Knowledge-based solution to dynamic optimization problems using cultural algorithms , 2001 .

[20]  Xin Yao,et al.  Stochastic ranking for constrained evolutionary optimization , 2000, IEEE Trans. Evol. Comput..

[21]  K. Deb.  An Efficient Constraint Handling Method for Genetic Algorithms , 2000 .

[22]  R. Reynolds,et al.  Using knowledge-based evolutionary computation to solve nonlinear constraint optimization problems: a cultural algorithm approach , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[23]  Rainer Storn,et al.  System design by constraint adaptation and differential evolution , 1999, IEEE Trans. Evol. Comput..

[24]  Zbigniew Michalewicz,et al.  Evolutionary Algorithms, Homomorphous Mappings, and Constrained Parameter Optimization , 1999, Evolutionary Computation.

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

[26]  Ivan Zelinka,et al.  Mechanical engineering design optimization by differential evolution , 1999 .

[27]  Robert G. Reynolds,et al.  Cultural algorithms: theory and applications , 1999 .

[28]  Riccardo Poli,et al.  New ideas in optimization , 1999 .

[29]  Robert G. Reynolds,et al.  CAEP: An Evolution-Based Tool for Real-Valued Function Optimization Using Cultural Algorithms , 1998, Int. J. Artif. Intell. Tools.

[30]  David H. Wolpert,et al.  No free lunch theorems for optimization , 1997, IEEE Trans. Evol. Comput..

[31]  Zbigniew Michalewicz,et al.  Handbook of Evolutionary Computation , 1997 .

[32]  R. Storn,et al.  On the usage of differential evolution for function optimization , 1996, Proceedings of North American Fuzzy Information Processing.

[33]  Man Systems,et al.  1996 Biennial Conference of the North American Fuzzy Information Processing Society - NAFIPS , 1996 .

[34]  Zbigniew Michalewicz,et al.  Evolutionary Algorithms for Constrained Parameter Optimization Problems , 1996, Evolutionary Computation.

[35]  Zbigniew Michalewicz,et al.  Genetic Algorithms + Data Structures = Evolution Programs , 1996, Springer Berlin Heidelberg.

[36]  Robert G. Reynolds,et al.  A Testbed for Solving Optimization Problems Using Cultural Algorithms , 1996, Evolutionary Programming.

[37]  Robert G. Reynolds,et al.  Evolutionary Programming IV: Proceedings of the Fourth Annual Conference on Evolutionary Programming , 1995 .

[38]  T. M. English.  Proceedings of the third annual conference on evolutionary programming: A.V. Sebald and L.J. Fogel, River Edge, NJ: World Scientific, ISBN 981-02-1810-9, 371 pages, hardbound, $78 , 1995 .

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

[40]  J. David Schaffer,et al.  Proceedings of the third international conference on Genetic algorithms , 1989 .

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

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

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

[44]  Jon Louis Bentley,et al.  Data Structures for Range Searching , 1979, CSUR.

[45]  James M. Gere,et al.  Analysis of framed structures , 1965 .