CEC/GECCO - Competition 2019 : Competition CEC/GECCO - Evolutionary Computation in Uncertain Environments: A Smart Grid Application
Call For Papers
Call for Participants
- This competition is a jointly CEC/GECCO 2019 competition. Therefore, contestants will be automatically participating in a competition at two major conferences in the field of CI, namely GECCO 2019 and CEC 2019.
- Notice that submission of papers or assistance to CEC by competition participants is not mandatory.
- GECCO participants will need to register an entry at https://ssl.linklings.net/conferences/gecco/ no later than April 3, 2019
- GECCO participants can also submit a competition abstract (two pages) describing their algorithms to be published in the GECCO Conference Companion Proceedings.
- Additionally, participants can submit full papers to the workshop Evolutionary Algorithms for Smart Grids (SmartEA) http://ci4energy.uni-paderborn.de/smartEA19/
April 3rd, 29:59 (GMT)- Mandatory register entry for GECCO https://ssl.linklings.net/conferences/gecco/
April 3rd, 29:59 (GMT)- Submission of two pages competition abstract
April 3rd, 29:59 (GMT)- Submission of full paper workshop
April 30th, 29:59 (GMT)
(Submission without paper)
Following the success of the previous edition at WCCI 2018 (http://www.gecad.isep.ipp.pt/WCCI2018-SG-COMPETITION/), we are relaunching this competition at major conferences in the field of computational intelligence. This CEC/GECCO 2019 competition proposes optimization of a centralized day-ahead energy resource management problem in smart grids under environments with uncertainty. This year we increased the difficulty by proving a more challenging case study, namely with a higher degree of uncertainty.
The competition provides a coherent framework where participants and practitioners of CI can test their algorithms to solve a real-world optimization problem in the energy domain with uncertainty consideration.
-Participants will propose and implement metaheuristic (e.g., evolutionary algorithms, swarm intelligence, etc.) to solve the energy resource management problem under uncertainty.
-The organizers provide a framework, implemented in MATALAB© 2014b 64 bits. The guidelines include the necessary information to understand the problem, how the solutions are represented, and how the fitness function is evaluated.
-20 independent trials should be performed in the framework by each participant.
how to submit an entry and how to evaluate them
-The winner will be the participant with the minimum ranking index, which is calculated as the average value over the 20 trials of the expected fitness value plus the standard deviation.
- Each participant is requested to put the text files corresponding to final results (see guideline document), as well as the implementation files (codes), into a zipped folder named
CEC2019_SG_AlgorithmName_ParticipantName.zip (e.g. CEC2019_SG_DE_Lezama.zip).
Fernando Lezama, GECAD, Polytechnic of Porto
Joao Soares, GECAD, Polytechnic of Porto
Zita Vale, Polytechnic of Porto
Jose Rueda, Delft University
Markus Wagner, Adelaide University