Metaheuristic optimization algorithms are nowadays being employed to solve a wide variety of optimization problems. These algorithms are not based on mathematical evidence and have mostly been developed by imitation of natural phenomenon. In this study, a web-based educational metaheuristics testing tool was developed. With this tool, the users are able to test Artificial Immune System and Artificial Bee Colony algorithms on Benchmark functions, observe the results of optimization by modifying the parameters for each algorithm, and at the same time perform optimization procedures by typing their own functions with their own constraints. In addition, information on the working steps of both algorithms are provided in the application.
Metaheuristic optimization algorithms are nowadays being employed to solve a wide variety of optimization problems. These algorithms are not based on mathematical evidence and have mostly been developed by imitation of natural phenomenon. In this study, a web-based educational metaheuristics testing tool was developed. With this tool, the users are able to test Artificial Immune System and Artificial Bee Colony algorithms on Benchmark functions, observe the results of optimization by modifying the parameters for each algorithm, and at the same time perform optimization procedures by typing their own functions with their own constraints. In addition, information on the working steps of both algorithms are provided in the application.
Primary Language | Turkish |
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Journal Section | Research Article |
Authors | |
Publication Date | February 1, 2014 |
Published in Issue | Year 2014 Volume: 20 Issue: 2 |