This repository provides the source code for the Improved Educational Competition Optimizer (IECO), a novel optimization algorithm designed for advanced engineering optimization tasks.

The IECO source code includes two distinct sets of benchmark test functions:

• Standard Benchmark Functions: Classical test functions commonly used for evaluating optimization algorithms.
• Shifted Benchmark Functions: Classical functions that have been shifted to avoid the bias towards the origin, aiding in better generalization and preventing overfitting.

The repository is structured into folders that can be executed directly using the provided main files for easy experimentation and testing.

• Early Stopping Mechanism: The improved version of IECO incorporates an early stopping feature implemented through two m files, enhancing the algorithm's efficiency and robustness.
• User-Friendly Implementation: The code is designed for easy integration and use in your own optimization experiments.

1. Clone the repository.
2. Navigate to the desired test function set.
3. Run the main file to start the optimization process.

Detailed documentation for running and modifying the code is provided within the comments of each file. For an in-depth explanation of the algorithm and its implementation, please refer to the upcoming publication.

For academic use, please cite our forthcoming paper:

IECO: An Improved Educational Competition Optimizer for State-of-the-Art Engineering Optimization
Authors: Xiaojie Tang#, Junbo Lian#, Ling Ma, Xincan Wu, Rui Zhong, Yujun Zhang, Huiling Chen

• School of Mechanical Engineering, Sichuan University Jinjiang College, Meishan 620680, PR China
• School of Mathematics and Computer Sciences, Zhejiang A & F University, Hangzhou 311300, PR China
• Graduate School of Information Science and Technology, Hokkaido University, Sapporo, Japan
• School of New Energy, Jingchu University of Technology, Jingmen, 448000, PR China
• School of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou 325035, PR China

#These authors contributed equally to this work.
Corresponding authors: Junbo Lian ([email protected]), Huiling Chen ([email protected])

Stay tuned for more updates and the publication of the full paper for further insights into the theoretical background and experimental results.