IEEE WCCI 2026 & GECCO 2026 (Joint Competition)
June 21 – June 26 – Maastricht, Netherlands (IEEE WCCI 2026) | July 13 – July 17 – San José, Costa Rica (GECCO 2026)
Organized by Polytechnic of Porto (ISEP)
Polytechnic of Porto (ISEP): Fernando Lezama, José Almeida, João Soares, Filipe Sousa, Zita Vale
Important: The use of the software platform is prohibited for purposes other than competition without a prior authorization of the organizing team.
Results Published: (TBD)
Final Rank Results
| Final Rank | Name | Affiliation, Country | Algorithm | Avg. Fitness | Avg. FEs | Rank Index |
| 1 IEEE CIS Prize – 500 $ | Jingao Liu, Chixin Xiao | Xiangtan University, China | SAGE_HPDE | 0.1605 (0.0046) | 2800 (0.5100) | 0.5146 |
| 2 IEEE CIS Prize – 300 $ | Kang Li, Jiaming Hu, Chixin Xiao | Xiangtan University, China | L-SHADE-OBL | 0.1631 (0.0227) | 2797 (0.5094) | 0.5321 |
| 3 IEEE CIS Prize – 200 $ | YuXiang Fu, JinGao Liu | Xiangtan University, China | AL_SHADE | 0.1646 (0.0335) | 2800 (0.5100) | 0.5436 |
| 4 | Jun Hu, Chixin Xiao | Xiangtan University, China | LSHADE_DimRed | 0.1983 (0.2692) | 1800 (0.2873) | 0.5565 |
| 5 | Jiahe Liu, Jiaming Hu, Chixin Xiao | Xiangtan University, China | MyLSHADE | 0.1754 (0.1088) | 2600 (0.4655) | 0.5743 |
| 6 | Jakub Kůdela | Brno University of Technology, Czech Republic | EA4Eig | 0.1949 (0.2457) | 2210 (0.3786) | 0.6243 |
| 7 | Jakub Kůdela | Brno University of Technology, Czech Republic | EA4Eig | 0.2124 (0.3678) | 1710 (0.2673) | 0.6350 |
| 8 | Jakub Kůdela | Brno University of Technology, Czech Republic | EA4Eig | 0.2047 (0.3137) | 2010 (0.3341) | 0.6478 |
| 9 | Jakub Kůdela | Brno University of Technology, Czech Republic | EA4Eig | 0.2185 (0.4102) | 1610 (0.2450) | 0.6552 |
| 10 | (a) Miguel Bethencourt Mayedo, (b) Yoan Martínez López, (a) Julio Madera Quintana, (c) Ansel Y. Rodríguez González | (a) Universidad de Camagüey, Cuba; (b) Universidad de Córdoba, Spain; (c) CICESE-UT3, Mexico | ARISE_jSO_Phase5 | 0.1921 (0.2261) | 2500 (0.4432) | 0.6693 |
| 11 | García Uzca Cristopher Fernando, Chillogalli Astudillo José Eduardo, Cando Naula Diego Jonnathan, Morquecho Salto Edgar Gonzalo, Torres Contreras Santiago Patricio, Astudillo Salinas Darwin Fabián | Department of Electrical Engineering, Electronics and Telecommunications (DEET), University of Cuenca, Ecuador | RDEx-SOP-NLPR | 0.1638 (0.0279) | 3500 0.6659 | 0.6938 |
| 12 | Jakub Kůdela | Brno University of Technology, Czech Republic | EA4Eig | 0.1926 (0.2296) | 2610 (0.4677) | 0.6973 |
| 13 | (a) Miguel Bethencourt Mayedo, (b) Yoan Martínez López, (a) Julio Madera Quintana, (c) Ansel Y. Rodríguez González | (a) Universidad de Camagüey, Cuba; (b) Universidad de Córdoba, Spain; (c) CICESE-UT3, Mexico | ARISE_jSO | 0.2148 (0.3844) | 2000 (0.3318) | 0.7162 |
| 14 | Jakub Kůdela | Brno University of Technology, Czech Republic | EA4Eig | 0.2313 (0.5001) | 1510 (0.2227) | 0.7229 |
| 15 | Diego Jonnathan Cando Naula, Edgar Gonzalo Morquecho Salto, José Eduardo Chillogalli Astudillo, Cristopher Fernando García Uzca, Santiago Patricio Torres Contreras, Darwin Fabián Astudillo | Department of Electrical Engineering, Electronics and Telecommunications (DEET), University of Cuenca, Ecuador | J-AHJ-LSHADE-RSP | 0.1816 (0.1523) | 3400 (0.6437) | 0.7960 |
| 16 | Jakub Kůdela | Brno University of Technology, Czech Republic | EA4Eig | 0.2482 (0.6181) | 1310 (0.1782) | 0.7963 |
| 17 | Jesse Palarus | TU Berlin, Germany | NL-SHADE-RSP_PWI | 0.1856 (0.1805) | 3275.5 (0.6159) | 0.7964 |
| 18 | Kai-Chen Tsai, Yu-An Lu | National Taiwan Normal University, Taiwan | Improved_LSHADE | 0.1658 (0.0417) | 4000 (0.7773) | 0.8190 |
| 19 | Jakub Kůdela | Brno University of Technology, Czech Republic | EA4Eig | 0.2569 (0.6786) | 1210 (0.1559) | 0.8345 |
| 20 | Jakub Kůdela | Brno University of Technology, Czech Republic | EA4Eig | 0,1912 0,2197 | 3310 (0.6236) | 0.8433 |
| 21 | Jakub Kůdela | Brno University of Technology, Czech Republic | EA4Eig | 0.1785 (0.1310) | 3810 (0.7350) | 0.8660 |
| 22 | (a) Raghav Thind, (a) Youran Sun, (b) Ling Liang, (a) Haizhao Yang | (a) University of Maryland, USA; (b) University of Tennessee, USA | LSHADE_LPSR_Frugal | 0.1743 (0.1014) | 3996 (0.7764) | 0.8778 |
| 23 | Jakub Kůdela | Brno University of Technology, Czech Republic | EA4Eig | 0.1875 (0.1933) | 3610 (0.6904) | 0.8837 |
| 24 | (a) (b) Ansel Y. Rodríguez González, (a) Marco Antonio Pérez Doimeadios, (c) Yoan Martínez López, (a) Lino Alberto Rodriguez Coayahuitl, (a) José Agustín Almaraz Damián, (d) Julio Madera | (a) CICESE, Mexico; (b) SECIHTI, Mexico; (c) Universidad de Córdoba, Spain; (d) Universidad de Camagüey, Cuba | RCEDPADA2500 | 0.2260 (0.4631) | 2500 (0.4432) | 0.9063 |
| 25 | Jakub Kůdela | Brno University of Technology, Czech Republic | EA4Eig | 0.2844 (0.8713) | 710 (0.0445) | 0.9159 |
| 26 | Jakub Kůdela | Brno University of Technology, Czech Republic | EA4Eig | 0.2890 (0.9031) | 610 (0.0223) | 0.9254 |
| 27 | Jakub Kůdela | Brno University of Technology, Czech Republic | EA4Eig | 0,2844 (0,8713) | 810 (0,0668) | 0,9381 |
| 28 | Jakub Kůdela | Brno University of Technology, Czech Republic | EA4Eig | 0.1784 (0.1302) | 4210 (0.8241) | 0.9543 |
| 29 | Chi-Yuan Ding, Wei-Yeh Ho, Yi-Hsuan Chao | Department of Computer Science and Information Engineering, National Taiwan Normal University, Taiwan | SA_LSHADE | 0.1598 (0.0000) | 4800 (0.9555) | 0.9555 |
| 30 | Jakub Kůdela | Brno University of Technology, Czech Republic | EA4Eig | 0.2844 (0.8713) | 910 (0.0891) | 0.9604 |
| 31 | Jakub Kůdela | Brno University of Technology, Czech Republic | EA4Eig | 0.3028 (1.0000) | 510 (0.0000) | 1.0000 |
| 32 | Jakub Kůdela | Brno University of Technology, Czech Republic | EA4Eig | 0.1710 (0.0782) | 4710 (0.9354) | 1.0136 |
| 33 | (a) Raghav Thind, (a) Youran Sun, (b) Ling Liang, (a) Haizhao Yang | (a) University of Maryland, USA; (b) University of Tennessee, USA | LSHADE_LPSR | 0.1668 (0.0489) | 4997 (0.9993) | 1.0482 |
| 34 | Hainan Zhang, Haoxiang Qin, Shixuan Zhou, Kaichen Chen, and Yi Xiang | South China University of Technology, China | Improved Memetic Algorithm (IMA) | 0.1683 (0.0597) | 5000 (1.0000) | 1.0597 |
| 35 | Tze-Hsiang, Tang | Schneider Electric Taiwan Co., Ltd., Taiwan | L-SHADE with jSO enhancements | 0.1715 (0.0818) | 5000 (1.0000) | 1.0818 |
| 36 | Chillogalli Astudillo José Eduardo, García Uzca Cristopher Fernando, Cando Naula Diego Jonnathan, Morquecho Salto Edgar Gonzalo, Torres Contreras Santiago Patricio, Astudillo Salinas Darwin Fabián | Department of Electrical Engineering, Electronics and Telecommunications (DEET), University of Cuenca, Ecuador | Multi-Start Nonlinear Success-History Adaptive Differential Evolution | 0.1720 (0.0852) | 5000 (1.0000) | 1.0852 |
| 37 | Dr. Vasundhara Mahajan, Mr. Vamshi Bhukya | Department of Electrical Engineering, Sardar Vallabhbhai National Institute of Technology, Surat, Gujarat – 395007, India | CL_HC2RCEDUMDA | 0.1826 (0.1592) | 5000 (1.0000) | 1.1592 |
| 38 | Bipul Gyawali, Saurav Aryal | Howard University, USA | FairMix-focused DE | 0.2469 (0.6087) | 3220.7 (0.6037) | 1.2125 |
| 39 | (a) (b) Ansel Y. Rodríguez González, (a) Marco Antonio Pérez Doimeadios, (c) Yoan Martínez López, (a) Lino Alberto Rodriguez Coayahuitl, (a) José Agustín Almaraz Damián, (d) Julio Madera | (a) CICESE, Mexico; (b) SECIHTI, Mexico; (c) Universidad de Córdoba, Spain; (d) Universidad de Camagüey, Cuba | RCEDPADA5000 | 0.1995 (0.2778) | 5000 (1.0000) | 1.2778 |
| 40 | Binti Kumari | Dayalbagh Educational Institute, Deemed to be University, Agra, Uttar Pradesh, India | HyDE-DF with RNN-RL adaptive ginv control | 0.2190 (0.4139) | 4700 (0.9332) | 1.3471 |
| 41 | Muhammad Waqar Hassan | Faculty of Mining, Safety Engineering and Automation Industry, Silesian University of Technology, Poland | Enhanced PSO with Opposition Learning and Restart Strategy | 0.2171 (0.4004) | 5000 (1.0000) | 1.4004 |
| 42 | Dumitru Novic | inZOR-ND Research, Independent | Bio-Adaptive Warm-Start Differential Evolution (BAWS-DE) | 0.2331 (0.5126) | 4789 (0.9530) | 1.4656 |
| 43 | Dr. Vasundhara Mahajan, Mr. Vamshi Bhukya | Department of Electrical Engineering, Sardar Vallabhbhai National Institute of Technology, Surat, Gujarat – 395007, India | GAPSO | 0.2375 (0.5432) | 5000 (1.0000) | 1.5432 |
| 44 | Dr. Vasundhara Mahajan, Mr. Vamshi Bhukya | Department of Electrical Engineering, Sardar Vallabhbhai National Institute of Technology, Surat, Gujarat – 395007, India | GAPSO | 0.2798 (0.8388) | 5000 (1.0000) | 1.8388 |
| 45 | Dr. Vasundhara Mahajan, Mr. Vamshi Bhukya | Department of Electrical Engineering, Sardar Vallabhbhai National Institute of Technology, Surat, Gujarat – 395007, India | DETLBO | 0.2863 (0.8845) | 5000 (1.0000) | 1.8845 |
| Honorable Mention | Michael Ibrahim | Cairo University, Egypt | FAIRHYBRID Random-start hybrid optimizer | 0.1554 (0.0000) | 82 (0.0000) | 0.0000 |
Competition Outline
Following the success of the previous editions at IEEE PES-GM, CEC, GECCO, and WCCI, we are launching another challenging edition of the competition at major conferences in the field of computational intelligence and power systems. This WCCI and GECCO 2026 competition challenges participants to develop benchmark evolutionary algorithms for optimizing energy pricing strategies in Local Energy Communities (LECs). Unlike traditional methods focused solely on cost minimization, this competition emphasizes fairness-aware pricing, where fairness metrics (e.g., Jain’s Fairness index, standard deviation of energy bills, Quality of Experience) guide the optimization process. The goal is to promote the design of metaheuristic algorithms that produce pricing strategies balancing technical efficiency and equitable cost distribution among community members.
Note: The track is developed to run under the same framework as past competitions.
Competition Goals
The competition has been held since 2017 at major conferences (the first competition was launched at IEEE PES GM) – Website: http://www.gecad.isep.ipp.pt/smartgridcompetitions.
We have been implementing variants of the benchmark problems, but have always used the same framework. This year, we implemented a novel framework for fairness-aware pricing optimization in energy communities (a relatively recent problem in the energy domain), using an evaluation criterion that includes the fitness value and the number of function evaluations (e.g., convergence).
Rules
- Participants will propose and implement metaheuristic algorithms (e.g., evolutionary algorithms, swarm intelligence, estimation of distribution algorithm, etc.) to solve the proposed track problem in the energy domain.
- The organizers provide a framework (Download), implemented in MATALAB© 2021a 64 bits, in which participants can easily test their algorithms (we also provide a hybrid-adaptive differential evolution algorithm implementation as an example). The guidelines (Download) include the necessary information to understand the problem, how the solutions are represented, and how the fitness function is evaluated. Also, we provide information on mathematical formulation regarding the objective function value and problem constraints. Those elements are common for all participants.
- A maximum number of “function evaluations” is considered for all algorithms. However, this year, the algorithms’ convergence properties, measured as the number of “functions evaluations”, are part of the evaluation criteria in the competition. Thus, participants should strive to obtain the lowest number of “function evaluations” as well.
- In addition, 20 independent trials should be performed in the framework by each participant.
How to Submit an Entry
– The winner will be the participant with the minimum ranking index in the proposed track, which is calculated as the sum of the normalized values of the average fitness value and the average number of function evaluations for the 20 trials. Possible outliers in the normalization will be handled by winsorizing the results.
– Each participant is kindly requested to put the text files corresponding to final results (see guidelines document), as well as the implementation files (codes), obtained by using a specific optimizer, into a zipped folder named GECCO_WCCI_2026_AlgorithmName_ParticipantName.zip
(e.g. GECCO_WCCI_2026_DE_JoseAlmeida.zip).
The participants should submit the files to the registration form (link) by 1st June 2026 (anywhere on Earth).
Important Remarks
- Notice that submission of papers or assistance to CEC and GECCO by competition participants is not mandatory.
- You can submit a paper to the WCCI-2026 Special Session on User-Centric Algorithms and Fair Applications using AI and Evolutionary Computation (Submit it here) – select Special Session: User-Centric Algorithms and Fair Applications using AI and Evolutionary Computation.
- You are also welcome to submit short descriptions of your algorithms and results as 2-page papers to be included in the GECCO Companion. This is voluntary: the submission deadline is TBD. Submit it here (Competition Entry Submissions)
IEEE CES PRIZE:
We are glad to announce that our competition will offer an IEEE Computational Intelligence Society (CIS) prize of a total of 1000 $:
- 500 $ for the participant with the best rank,
- 300 $ for the second best,
- 200 $ for the third best.
Good luck, and stay tuned. Thanks!
Submit your results by 1st June 2026 (anywhere on Earth)
Further Related Bibliography
- [1] F., Lezama, J. Soares, Z. Vale, J. Rueda, S. Rivera, & I. Elrich, 2017 IEEE Competition on modern heuristic optimizers for smart grid operation: Testbeds and results. Swarm and evolutionary computation, 44, 420-427, 2019.
- [2] F. Lezama, J. Soares, P. Hernandez-Leal, M. Kaisers, T. Pinto, and Z. Vale, Local Energy Markets: Paving the Path Towards Fully Transactive Energy Systems, IEEE Transaction on Power Systems, IEEE (2018).
- [4] F. Lezama, J. Soares, E. Munoz de Cote, L. E. Sucar, and Z. Vale, “Differential Evolution Strategies for Large-Scale Energy Resource Management in Smart Grids,” in GECCO ’17: Genetic and Evolutionary Computation Conference Companion Proceedings, 2017.
- [5] J. Almeida, J. Soares, F. Lezama, S. Limmer, T. Rodemann, and Z. Vale, “A systematic review of explainability in computational intelligence for optimization,” Computer Science Review, vol. 57, p. 100764, Aug. 2025.
- [6] J. Soares et al., “Review on fairness in local energy systems,” Applied Energy, vol. 374, p. 123933, Nov. 2024.
- [7] F. Lezama, F. Doria, and J. Soares, “Fair Pricing Optimization in Energy Communities with Differential Evolution,” in Proceedings of the International Workshop on AI Systems for the Environment (AISE-2025), 2025, pp. 61–70.
- [8] J. Almeida, J. Soares, E. Aliyan, S. Limmer, R. Faia, and S. Ramos, “Fairness Index Analysis in Local Energy Communities Considering Electric Vehicles and Energy Storage,” in Proceedings of the VII Ibero-American Congress of Smart Cities, ICSC-Cities 2024, 12–14 November, San Carlos, Costa Rica, D. Rossit, P. Moreno-Bernal, and C. E. Torres-Aguilar, Eds., Singapore: Springer Nature Singapore, 2025, pp. 175–189.
Organizers
