Source code and Experimental Results of paper "VGWO: Variant Grey Wolf Optimizer with High Accuracy and Low Time Complexity".

#catalogue:

    1. source code:
            """
            The experimental framework and programs used for comparison were 
            implemented in Python3.9. This folder includes the following four '. py' files 
            that can be run independently, and their purposes are as follows.
            """

            Calculating ARV.py: Calculate the performance (ARV) in 25 sets of parameter combinations;

            Calculating st^la.py: Calculate the scheduling time of each benchmark function VGWO;

            engineering_cases.py: Three engineering examples are optimized with VGWO;

            experimental.py: Optimizing 19 benchmark functions with VGWO;

            IMODE.py: Solving 19 Benchmark Functions with 2020CEC Winner IMODE;


    2. result:
            """
            The experimental results were obtained by running on a computer with a 2.90 GHz 
            Intel i7-10700 CPU and 16 GB RAM. These results are reproducible. 
            This folder mainly includes the following contents.
            """

            Appendix 1: result of Orthogonal experimental. The details are described in section 4.2 of the paper;

            result of Calculating ARV;

            result of Calculating st^la;

            result of engineering_cases;

            result of experimental;

            result of IMODE;