Special Session & Competition on Real-Parameter Single Objective Optimization at CEC-2013, Cancun, Mexico 21-23 June 2013

If you face any difficulties, please inform me ( epnsugan@ntu.edu.sg  ).

  1. Call for papers

  2. J. J. Liang, B-Y. Qu, P. N. Suganthan, Alfredo G. Hernández-Díaz, "Problem Definitions and Evaluation Criteria for the CEC 2013 Special Session and Competition on Real-Parameter Optimization", Technical Report 201212, Computational Intelligence Laboratory, Zhengzhou University, Zhengzhou China  and  Technical Report, Nanyang Technological University, Singapore, January 2013.

  3. To download, Matlab, C, JAVA,  & Data files. please follow the link:  http://web.mysites.ntu.edu.sg/epnsugan/PublicSite/Shared Documents/Forms/AllItems.aspx to CEC2013 folder.

  4. The R-package is available from:    http://cran.r-project.org/web/packages/cec2013/cec2013.pdf          It can be useful for Linux, Mac, etc. For queries, please contact the maintainer:  Mauricio Zambrano-Bigiarini    mzb.devel@gmail.com

  5. Comparison of Algorithms ( Prepared by Ilya Loshchilov , Thomas Stuetzle & Tianjun Liao )


Accepted Papers

  1. Benchmark Results for a Simple Hybrid Algorithm on the CEC 2013 Benchmark Set for Real parameter Optimization [#1566] . . Tianjun Liao and Thomas Stuetzle   Universite Libre de Bruxelles (ULB), IRIDIA, Belgium (Codes-Results available, as icmaesils)

  2. CMA-ES with Restarts for Solving CEC 2013 Benchmark Problems [#1318] . Ilya Loshchilov Ecole Polytechnique Federale de Lausanne, Laboratory of Intelligent Systems, Switzerland (Codes-Results available, asNBIPOPaCMA)

  3. Dynamically updated Region Based Memetic Algorithm for the 2013 CEC Special Session and  Competition on Real Parameter Single Objective Optimization [#1617] . . Benjamin Lacroix, Daniel Molina and Francisco Herrera   Universidad de Granada, Spain; Universidad de Cadiz, Spain  (Codes-Results available, as DRMA-LSch-CMA)

  4. Evaluating the performance of SHADE on CEC 2013 benchmark problems [#1652] . . Ryoji Tanabe and Alex Fukunaga  The University of Tokyo, Japan (Codes-Results available, as SHADE_CEC2013)

  5. A Genetic Algorithm for Solving the CEC’2013 Competition Problems on Real-Parameter Optimization [#1132] . Saber Elsayed, Ruhul Sarker and Daryl Essam     UNSW at Canberra, Australia

  6. Mean-Variance Mapping Optimization for Solving the IEEE-CEC 2013 Competition Problems [#1284] . . Jose Rueda and Istvan Erlich  University Duisburg-Essen, Germany  (Codes-Results available, as MVMO-SH_CEC2013)

  7. A Self-Adaptive Heterogeneous PSO for Real-Parameter Optimization [#1267] . Filipe Nepomuceno and Andries Engelbrecht, University of Pretoria, South Africa

  8. Real Parameter Single Objective Optimization using Self-Adaptive Differential Evolution Algorithm with more Strategies [#1381] . Janez Brest, Borko Boskovic, Ales Zamuda, Iztok Fister and Efren Mezura-Montes    University of Maribor, Slovenia; Universidad Veracruzana, Mexico

  9. Structured Population Size Reduction Differential Evolution with Multiple Mutation Strategies on  CEC 2013 Real Parameter Optimization [#1393] . . Ales Zamuda, Janez Brest and Efren Mezura-Montes University of Maribor, Slovenia; University of Veracruz, Mexico  (Codes-Results available, as SPSRDEMMS)

  10. Differential Evolution with Concurrent Fitness Based Local Search [#1476] . Ilpo Poikolainen and Ferrante Neri,    University of Jyvaskyla, Finland

  11. Competitive Differential Evolution Applied to CEC 2013 Problems [#1110] . Josef Tvrdik and Radka Polakova      University of Ostrava, Czech Republic. (Codes-Results available, as CEC2013_b6e6rl)

  12. Investigation of Self-adaptive Differential Evolution on the CEC-2013 Single-Objective Continuous  Optimization Testbed [#1750] . . A. K. Qin, Xiaodong Li, Hong Pan and Siyu Xia  RMIT University, Australia; Southeast University, China  

  13. Teaching and Learning based Differential Evoltuion with Self Adaptation for Real Parameter Optimization  [#1732] . . Subhodip Biswas, Souvik Kundu, Swagatam Das and Athanasios Vasilakos  Jadavpur University, India; Indian Statistical Institute, India; Kuwait University, Kuwait

  14. A CMA-ES Super-fit Scheme for the Re-sampled Inheritance Search [#1093] . . Fabio Caraffini, Giovanni Iacca, Ferrante Neri, Lorenzo Picinali and Ernesto Mininno   De Montfort University, United Kingdom; INCAS3, Netherlands; University of Jyvaskyla, Finland

  15. The Parameter-Less Evolutionary Search for Real-Parameter Single Objective Optimization [#1159]   Gregor Papa and Jurij Silc. . Jozef Stefan Institute, Slovenia

  16. Differential Evolution on the CEC-2013 Single-Objective Continuous Optimization Testbed [#1733]  A  K. Qin and Xiaodong Li . . RMIT University, Australia

  17. The Continuous Differential Ant-Stigmergy Algorithm Applied on Real-Parameter Single Objective  Optimization Problems [#1238] . . Peter Korosec and Jurij Silc    Jozef Stefan Institute, Slovenia

  18. Population’s Variance-Based Adaptive Differential Evolution for Real Parameter Optimization  [#1285] . Leandro Coelho, Helon Ayala and Roberto Freire  Pontifical Catholic University of Parana - PUCPR, Brazil  (Codes-Results available, as PVADE)

  19. Super-fit Multicriteria Adaptive Differential Evolution [#1122] . . Fabio Caraffini, Ferrante Neri, Jixiang Cheng, Gexiang Zhang, Lorenzo Picinali, Giovanni Iacca and Ernesto Mininno   De Montfort University, United Kingdom; University of Jyvaskyla, Finland; Southwest Jiaotong University,  China; INCAS3, Netherlands

  20. Differential Evolution with Automatic Parameter Configuration for Solving the CEC2013 Competition  on Real-Parameter Optimization [#1148] . Saber Elsayed, Ruhul Sarker and Tapabrata Ray  UNSW at Canberra, Australia 

  21. Differential Evolution: Performances and Analyses [#1676] . . . . Nikhil Padhye, Pulkit Mittal and Kalyanmoy Deb  MIT, United States of America; IIT K, India

  22. Testing A Particle Swarm Optimization and Artificial Bee Colony Hybrid Algorithm on The CEC13  Benchmarks [#1502] . Mohammed El-Abd  American University of Kuwait, Kuwait

  23. Standard Particle Swarm Optimisation 2011 at CEC-2013: A baseline for future PSO improvements    Mauricio Zambrano-Bigiarini, Maurice Clerc and Rodrigo Rojas     Institute for Environment and Sustainability. Joint Research Centre, European Commission, Italy;   Independent Consultant, France


Paper Submission

When submitting, please make sure you select "Real Parameter Single Objective Optimization" as the "Main Research Topic".

Paper Submission Deadline

We will follow the deadlines as determined by CEC 2013 which is now extended to March 2013 as the final - firm deadline.

Updated on  29th Jan 2013:

Considering the suggestions from the  researchers, we updated our competition as follows:

1. Error value smaller than 10-8 will be taken as zero.


2. 50D is added in the competition. Considering the limited time, results of 10D and 30D problems are acceptable for the review submission. However, 50D should be included in the final version. Thus 28*3 (10D, 30D and 50D) files should be zipped and sent to the organizers after the final version of the paper is submitted.


3. Equations of novel composition functions are modified for ease of understanding.

4. Some bugs have been modified:

(1) Codes for problems 3 and 4 were inconsistent with the report.  Problem 3 is bent_cigar while Problem 4 is discus_func. The report has been modified.

(2) For cf05, it is similar to cf04, not cf02. The report has been modified.

(3) For cf08, lamda_5=0.1. The report has been modified.

(4) Equations for Tosz, Functions 7, 14, 15, 17, 19, 21 are corrected in the report to be consistent with the code.

(5) In the code, "sphere_func(x,&fit[i],nx,&Os[i*nx],&Mr[i*nx*nx],1)" is modified to "sphere_func(x,&fit[i],nx,&Os[i*nx],&Mr[i*nx*nx],0)";


5. A mistake in the technical report (page 35) is corrected:
"c)  The complete computing time for the algorithm with 200000 evaluations of the same D dimensional benchmark function 3 is T2. "
Here  "benchmark function 3" should be "benchmark function
14" (the same as b).

Problems 3,4,21,27,28 should be run again due to the changes effected on 29th of Jan.


For Linux Users:

Please change %xx in fscanf and fprintf and do not use "WINDOWS.H".


We thank Dr. Thomas Stuetzle for suggesting items 1 & 2, and Dr Janez Brest for his comment on Linux.



Updated on  15th February 2013:


We thank Dr. Thomas Stuetzle and Dr Tianjun Liao for suggesting to change codes used to compute time T0 so that C compilers will not be able to optimize and eliminate the for-loop. This change affects only T0, not the benchmark problems.