List of References on Evolutionary Multiobjective Optimization

Maintained by

Carlos A. Coello Coello
ccoello@cs.cinvestav.mx
CINVESTAV-IPN
Sección de Computación
Departamento de Ingeniería Eléctrica
Av. Instituto Politécnico Nacional No. 2508
Col. San Pedro Zacatenco
México, D.F. 07300

Last Update: August 21st, 2002

(Keep in mind that this list is constantly being updated)

Author: A B C D E F H I J K L M N O P Q R S T U V W X Y Z

    A

  1. Robin Allenson. Genetic algorithms with gender for multi-function optimisation, Technical Report EPCC-SS92-01, Edinburgh Parallel Computing Centre, Edinburgh, Scotland, 1992.

  2. P. Alotto, A. V. Kuntsevitch, Ch. Magele, G. Molinari, C. Paul, K. Preis, M. Repetto, and K. R. Richter. Multiobjective Optimization in Magnetostatics: A Proposal for Benchmark Problems. Technical report, Institut für Grundlagen und Theorie Electrotechnik, Technische Universität Graz, Graz, Austria, 1996. http://www-igte.tu-graz.ac.at/team/berl01.htm

  3. Murray B. Anderson and Glenn A. Gerbert. Using Pareto Genetic Algorithms for Preliminary Subsonic Wing Design, Technical Report AIAA-96-4023-CP, AIAA, Washington, D.C., 1996.

  4. Johan Andersson. A Survey of Multiobjective Optimization in Engineering Design, Technical Report No. LiTH-IKP-R-1097, Department of Mechanical Engineering, Linköping University, 2000.

    5. B

  5. A. D. Belegundu and P. L. N. Murthy. A New Genetic Algorithm for Multiobjective Optimization. Technical Report No. AIAA-96-4180-CP, AIAA, Washington, D.C., 1996.

  6. P. J. Bentley and J. P. Wakefield. An Analysis of Multiobjective optimization within Genetic Algorithms, Technical Report ENGPJB96, University of Huddersfield, UK, 1996.

  7. To Thanh Binh. A multiobjective evolutionary algorithm: The study cases, Technical report, Institute for Automation and Communication, Barleben, Germany, January 1999.

  8. To Thanh Binh, Urlich Korn, and J. Kliche. Evolution Strategy Toolbox for use with MATLAB, Technical report, Institute of Automation, University of Magdeburg, Germany, March 1996.

  9. Tobias Blickle, Jürgen Teich, and Lothar Thiele. System-level synthesis using evolutionary algorithms, Technical Report TIK Report-Nr. 16, Computer Engineering and Communication Networks Lab (TIK), Swiss Federal Institute of Technology (ETH), Gloriastrasse 35, 8092 Zurich, April 1996.

  10. Pedro Castro Borges and Michael Pilegaard Hansen. A basis for future successes in multiobjective combinatorial optimization. Technical Report IMM-REP-1998-8, Institute of Mathematical Modelling, Technical University of Denmark, March 1998.

  11. Jürgen Branke, Thomas Kaußler, and Hartmut Schmeck. Guiding Multi Objective Evolutionary Algorithms Towards Interesting Regions, Technical Report 398, Institute für Angewandte Informatik und Formale Beschreibungsverfahren, Universität Karlsruhe, Karlsruhe, Germany, February 2000.

    12. C

  12. Alain Cardon and Jean-Philippe Vacher. Algorithmes Génétiques dans un Système Multi-Agents pour l'Ordonnancement. Technical report, Crihan, 1998. (In French).

  13. Alain Cardon and Jean-Philippe Vacher. Rapport Technique pour Ouverture de Compte au Crihan sur Machine Parallèle Illiac8. Technical report, Crihan, 1998. http://www.crihan.fr (In French).

  14. T. J. Chang, N. Meade, and J. E. Beasley. Heuristics for Cardinality Constrained Portfolio Optimization, Technical report, The Management School, Imperial College, London SW7 2AZ, England, May 1998.

  15. Kay Chen Tan and Yun Li. Multi-Objective Genetic Algorithm Based Time and Frequency Domain Design Unification of Linear Control Systems, Technical Report CSC-97007, Department of Electronics and Electrical Engineering, University of Glasglow, Glasglow, Scotland, 1997.

  16. Xianming Chen. Pareto Tree Searching Genetic Algorithm: Approaching Pareto Optimal Front by Searching Pareto Optimal Tree. Technical Report NK-CS-2001-002, Department of Computer Science, Nankai University, Tianjin, China, 2001

  17. Carlos A. Coello Coello. An Updated Survey of GA-Based Multiobjective Optimization Techniques, Technical Report Lania-RD-98-08, Laboratorio Nacional de Informática Avanzada (LANIA), Xalapa, Veracruz, México, December 1998.

    18. D

  18. Kalyanmoy Deb. Multi-Objective Genetic Algorithms: Problem Difficulties and Construction of Test Problems, Technical Report CI-49/98, Dortmund: Department of Computer Science/LS11, University of Dortmund, Germany, 1998.

  19. Kalyanmoy Deb. Multi-Objective Evolutionary Algorithms: Introducing Bias Among Pareto-Optimal Solutions KanGAL report 99002, Indian Institute of Technology, Kanpur, India, 1999.

  20. Kalyanmoy Deb. Non-linear goal programming using Multi-Objective Genetic Algorithms, Technical Report CI-60/98, Dortmund: Department of Computer Science/LS11, University of Dortmund, Germany, 1999.

  21. Kalyanmoy Deb, Samir Agrawal, Amrit Pratab, and T. Meyarivan. A Fast Elitist Non-Dominated Sorting Genetic Algorithm for Multi-Objective Optimization: NSGA-II, KanGAL report 200001, Indian Institute of Technology, Kanpur, India, 2000.

  22. Kalyanmoy Deb and T. Meyarivan. Constrained Test Problems for Multi-Objective Evolutionary Optimization, KanGAL report 200005, Indian Institute of Technology, Kanpur, India, 2000

  23. Kalyanmoy Deb and Tushar Goyal. Controlled Elitist Non-dominated Sorting Genetic Algorithms for Better Convergence, KanGAL report 200004, Indian Institute of Technology, Kanpur, India, 2000

  24. Kalyanmoy Deb and Tushar Goyal. Multi-Objective Evolutionary Algorithms for Engineering Shape Design, KanGAL report 200003, Indian Institute of Technology, Kanpur, India, 2000

  25. Kalyanmoy Deb, A. Patrap, and S. Moitra. Mechanical Component Design for multi-objective using Elitist non-dominated sorting GA, KanGAL report 200002, Indian Institute of Technology, Kanpur, India, 2000

  26. Kalyanmoy Deb, Lothar Thiele, Marco Laumanns and Eckart Zitzler. Scalable Test Problems for Evolutionary Multi-Objective Optimization, TIK-Report No.112, Computer Engineering and Networks Laboratory (TIK), Swiss Federal Institute of Technology (ETH) Zurich, July, 2001

    27. E

  27. Matthias Ehrgott and Xavier Gandibleux. An Annotated Bibliography of Multi-objective Combinatorial Optimization, Technical Report 62/2000, Fachbereich Mathematik, Universitat Kaiserslautern, Kaiserslautern, Germany, 2000.

    28. F

  28. P.J. Fleming and R.C. Purshouse. Genetic Algorithms in Control Systems Engineering, Technical Report No. 789, Departament of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, UK, May 2001.

  29. Carlos M. Fonseca and Peter J. Fleming. An overview of evolutionary algorithms in multiobjective optimization, Technical report, Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, U. K., 1994.

  30. Carlos M. Fonseca and Peter J. Fleming. Multiobjective Optimization and Multiple Constraint Handling with Evolutionary Algorithms I: A Unified Formulation, Technical Report 564, University of Sheffield, Sheffield, UK, January 1995.

  31. Carlos M. Fonseca and Peter J. Fleming. Multiobjective Optimization and Multiple Constraint Handling with Evolutionary Algorithms II: Application Example, Technical Report 565, University of Sheffield, Sheffield, UK, January 1995.

    32. G

  32. Caroline Gagné, Wilson L. Price, and Marc Gravel. Scheduling a Single Machine with Sequence Dependent Setup Time Using Ant Colony Optimization. Technical Report 2001-003, Faculté des Sciences de L'Administration, Université Laval, Québec, Canada, April 2001. Available on line .

  33. Marc Gravel, Wilson L. Price, and Caroline Gagné. Scheduling Continuous Casting of Aluminum Using a Multiple-Objective Ant Colony Optimization Metaheuristic. Technical Report 2001-004, Faculté des Sciences de L'Administration, Université Laval, Québec, Canada, April 2001. Available on line.

    34. H

  34. Michael Pilegaard Hansen. Generating a Diversity of Good Solutions to a Practical Combinatorial Problem using Vectorized Simulated Annealing. Technical report, Institute of Mathematical Modelling, Technical University of Denmark, August 1997. Working Paper.

  35. Jeffrey Horn and Nicholas Nafpliotis. Multiobjective Optimization using the Niched Pareto Genetic Algorithm, Technical Report IlliGAl Report 93005, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA, 1993.

  36. Evan J. Hughes. Multi-Objective Probabilistic Selection Evolutionary Algorithm. Technical Report DAPS/EJH/56/2000, Department of Aerospace, Power, & Sensors, Cranfield University, RMCS, Shrivenham, UK, SN6 8LA, September 2000 .

    37. I

    J

  37. Arne Jansson, Petter Krus, and Jan-Ove Palmberg. Optimisation of fluid power systems with two alternative non-derivative methods. Technical Report LiTH-IDA-R-94-29, Department of Mechanical Engineering, Linköping University, S-581 83 Linköping, Sweden, 1994.

  38. Andrzej Jaszkiewicz. Genetic local search for multiple objective combinatorial optimization, Technical Report RA-014/98, Institute of Computing Science, Poznan University of Technology, 1998.

  39. Andrzej Jaszkiewicz. On the performance of multiple objective genetic local search on the 0/1 knapsack problem. a comparative experiment, Technical Report RA-002/2000, Institute of Computing Science, Poznan University of Technology, Poznań, Poland, July 2000.

  40. Andrzej Jaszkiewicz, A comparative study of multiple-objective metaheuristics on the bi-objective set covering problem and the Pareto memetic algorithm, Research report, Institute of Computing Science, Poznan University of Technology, RA-003/01, 2001, Poznan, Poland, 2001 .

    41. K

  41. Nazan Khan, David E. Goldberg and Martin Pelikan. Multi-Objective Bayesian Optimization Algorithm, Technical Report No. 2002009, Illinois Genetic Algorithms Laboratory, University of Illinois at Urbana-Champaign, Urbana, Illinois, March 2002 .

  42. Soon-Thiam Khu. Automatic Calibration of NAM Model with Multi-Objectives Consideration, Technical Report 1298-1, National University of Singapore/Danish Hydraulic Institute, December 1998.

    43. L

  43. William B. Langdon. Data Structures and Genetic Programming. Research Note RN/95/70, University College London, Gower Street, London WC1E 6BT, UK, September 1995.

  44. William B. Langdon. Evolving data structures using genetic programming, Research Note RN/95/1, University College London, Gower Street, London WC1E 6BT, UK, January 1995.

  45. William B. Langdon. Pareto, Population Partitioning, Price and Genetic Programming, Research Note RN/95/29, University College London, Gower Street, London WC1E 6BT, UK, April 1995.

  46. William B. Langdon. Scheduling Maintenance of Electrical Power Transmission Networks Using Genetic Programming. Research Note RN/96/49, University College London, Gower Street, London WC1E 6BT, UK, June 1996.

  47. William B. Langdon. Using Data Structures within Genetic Programming. Research Note RN/96/1, University College London, Gower Street, London WC1E 6BT, UK, January 1996.

  48. William B. Langdon. Using Data Structures within Genetic Programming, In John R. Koza, David E. Goldberg, David B. Fogel, and Rick L. Riolo, editors, Genetic Programming 1996: Proceedings of the First Annual Conference, pages 141-148, Stanford University, CA, USA, 28-31 July 1996. MIT Press.

  49. Marco Laumanns, Günter Rudolph, and Hans-Paul Schwefel. Approximating the Pareto Set: Concepts, Diversity Issues, and Performance Assessment, Technical Report CI-72/99, Dortmund: Department of Computer Science/LS11, University of Dortmund, Germany, March 1999. ISSN 1433-3325.

  50. Marco Laumanns, Lothar Thiele, Kalyanmoy Deb and Eckart Zitzler On the Convergence and Diversity-Preservation Properties of Multi-Objective Evolutionary Algorithms, Technical Report 108, Computer Engineering and Networks Laboratory (TIK), Swiss Federal Institute of Technology (ETH) Zurich, Gloriastrasse 35, CH-8092 Zurich, Switzerland, May 2001.

    51. M

  51. Simon Mardle, Sean Pascoe, and Mehrdad Tamiz. An investigation of genetic algorithms for the optimisation of multi-objective fisheries bioeconomic models. Technical Report 136, Centre for the Economics and Management of Aquatic Resources, University of Portsmouth, 1998.

  52. Carlos E. Mariano and Eduardo Morales. A Multiple Objective Ant-Q Algorithm for the Design of Water Distribution Irrigation Networks, Technical Report HC-9904, Instituto Mexicano de Tecnologıa del Agua, June 1999.

  53. Carlos E. Mariano and Eduardo Morales. A New Distributed Reinforcement Learning Algorithm for Multiple Objective Optimization Problems Technical Report HC-200001, Instituto Mexicano de Tecnologıa del Agua, January 2000.

    54. N

    O

    P

  54. Michael Pilegaard Hansen and Andrzej Jaszkiewicz. Evaluating the quality of approximations to the non-dominated set, Technical Report IMM-REP-1998-7, Technical University of Denmark, March 1998.

  55. R.C. Purshouse and P.J. Fleming. The Multi-Objective Genetic Algorithm Applied to Benchmark Problems---An Analysis, Technical Report No. 796, Departament of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, UK, August 2001 .

  56. R.C. Purshouse and P.J. Fleming. Elitism, Sharing and Ranking Choices in Evolutionary Multi-Criterion Optimisation, Technical Report No. 815, Departament of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, UK, January 2002 .

    57. Q

    R

  57. Brian J. Reardon. Fuzzy Logic vs. Niched Pareto Multiobjective Genetic Algorithm Optimization: Part I. Schaffer's F2 Problem, Technical Report LA-UR-97-3675, Los Alamos National Laboratory, Los Alamos, New Mexico, September 1997.

  58. Brian J. Reardon. Fuzzy Logic vs. Niched Pareto Multiobjective Genetic Algorithm Optimization: Part II. A Simplified Born-Mayer Problem, Technical Report LA-UR-97-3676, Los Alamos National Laboratory, Los Alamos, New Mexico, September 1997.

  59. Brian J. Reardon. Optimization of Densification Modeling Parameters of Beryllium Powder using a Fuzzy Logic Based Multiobjective Genetic Algorithm, Technical Report LA-UR-98-1036, Los Alamos National Laboratory, Los Alamos, New Mexico, March 1998.

  60. Brian J. Reardon. Optimization of Micromechanical Densification Modeling Parameters For Copper Powder using a Fuzzy Logic Based Multiobjective Genetic Algorithm, Technical Report LA-UR-98-0419, Los Alamos National Laboratory, Los Alamos, New Mexico, January 1998.

    61. S

  61. M. Schwab, D. A. Savic, and G. A. Walters. Multi-Objective Genetic Algorithm for Pump Scheduling in Water Supply Systems, Technical Report 96/02, Centre For Systems And Control Engineering, School of Engineering, University of Exeter, Exeter, United Kingdom, 1996.

  62. Fatma Sibel Salman, Jayan Kalagnanam, and Sesh Murthy. Heuristics for Solving the Bicriteria Sparse Multiple Knapsack Problem. Technical Report RC 21059, IBM T.J. Watson Research Center, 1997.

  63. Dragan A. Savic, Godfrey A. Walters, and Martin Schwab. Multiobjective Genetic Algorithms for Pump Scheduling in Water Supply, In AISB International Workshop on Evolutionary Computing. Lecture Notes in Computer Science 1305, pages 227-236, Berlin, April 1997. Springer-Verlag.

  64. N. Srinivas and Kalyanmoy Deb. Multiobjective optimization using nondominated sorting in genetic algorithms. Technical report, Department of Mechanical Engineering, Indian Institute of Technology, Kanput, India, 1993.

    65. T

    U

    V

  65. David A. Van Veldhuizen and Gary B. Lamont. Multiobjective Evolutionary Algorithm Research: A History and Analysis, Technical Report TR-98-03, Department of Electrical and Computer Engineering, Graduate School of Engineering, Air Force Institute of Technology, Wright-Patterson AFB, Ohio, 1998.

    66. W

  66. D. S. Weile and E. Michielssen. Integer coded Pareto genetic algorithm design of constrained antenna arrays. Electronics Letters, 32(19):1744-1745, September 1996.

  67. D. S. Weile, E. Michielssen, and D. E. Goldberg. Genetic algorithm design of Pareto optimal broadband microwave absorbers. IEEE Transactions on Electromagnetic Compatibility, 38(3):518-525, August 1996.

  68. D. S. Weile and E. Michielssen. Integer coded Pareto genetic algorithm design of constrained antenna arrays. Technical Report CCEM-13-96, Electrical and Computer Engineering Department, Center for Computational Electromagnetics, University of Illinois at Urbana-Champaign, November 1996.

  69. D. S. Weile, E. Michielssen, and D. E. Goldberg. Genetic algorithm design of pareto optimal broad-band microwave absorbers. Technical Report CCEM-4-96, Electrical and Computer Engineering Department, Center for Computational Electromagnetics, University of Illinois at Urbana-Champaign, May 1996.

    70. X

    Y

    Z

  70. Eckart Zitzler, Kalyanmoy Deb, and Lothar Thiele. Comparison of Multiobjective Evolutionary Algorithms: Empirical Results, Technical Report 70, Computer Engineering and Networks Laboratory (TIK), Swiss Federal Institute of Technology (ETH) Zurich, Gloriastrasse 35, CH-8092 Zurich, Switzerland, December 1999.

  71. Eckart Zitzler and Lothar Thiele. An Evolutionary Algorithm for Multiobjective Optimization: The Strength Pareto Approach, Technical Report 43, Computer Engineering and Communication Networks Lab (TIK), Swiss Federal Institute of Technology (ETH), Zurich, Switzerland, May 1998.

  72. Eckart Zitzler, Marco Laumanns and Lothar Thiele. SPEA2: Improving the Strength Pareto Evolutionary Algorithm, Technical Report 103, Computer Engineering and Networks Laboratory (TIK), Swiss Federal Institute of Technology (ETH) Zurich, Gloriastrasse 35, CH-8092 Zurich, Switzerland, May 2001.

    73. Acknowledgments

    We acknowledge partial support from REDII-CONACyT and LANIA in the development, expansions and maintenance of this repository of information.

    For corrections and/or updates on current information or to add your technical report, please contact:
    Dr. Carlos A. Coello Coello