Python code for "Multi-fidelity Meta-optimization for Nature Inspired Optimization Algorithms"
收藏Mendeley Data2020-05-02 更新2026-04-09 收录
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资源简介：
The python code is used in the manuscript "Multi-fidelity Meta-optimization for Nature Inspired Optimization Algorithms" submitted to "Applied soft computing". The programming environment is: Python 3.6 or higher. The folders in the package include: 1. algorithms: Basic algorithms, including base class 'Algorithm' and [CS, DE, FOA, GWO, KH, PSO, SSA, WWO, WOA]. 2. applications: An engineering application: source term estimation. 3. benchmarks: Test functions, including base class 'Benchmark', basic test functions and 'CEC2014 Benchmark Suite'. 4. demo: Examples. 5. parameter_tuning: Multi-fidelity meta-NIOs and optimized-NIOs. If you prefer using the command line to run the program, please do not forget to manually add the working directory to 'sys.path'.
创建时间：
2020-05-02
