New Artificial Landscape for Single-Objective Problems and Validation of Evolutionary Algorithms
Publish place: 5th International Conference on knowledge based research in Computer engineering and Information Technology
Publish Year: 1396
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
COMCO04_008
تاریخ نمایه سازی: 17 آبان 1396
Abstract:
In general terms, optimization means to improve the state of something; Having a function f(x) in optimization, we want to find an argument x whose relevant cost is optimum (usually minimum). The Test Functions, which known as Artificial Landscapes in Applied Mathematic, are utilized for assessing features of optimization algorithms such: convergence speed, accuracy, robustness and their total functionality. Single-objective optimization algorithms are the underlying basis to more sophisticated algorithms such: multi-objective optimization algorithms, niching, constrained optimization algorithms, etc. These functions are also used for testing of evolutionary algorithms (generally optimization). The aim of presenting this paper is to implement a sort of Test Function for single-objective optimization problems and validating of evolutionary algorithms. Acquired results indicate that, the proposed test function is able to perform optimization operation and validating evolutionary algorithms well.
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Authors
S. Muhammad Hossein Mousavi
Department of Computer Engineering, Bu Ali Sina University, Hamadan, Iran
Vladimir S.Myasnichenko
Department of Physics, Tver State University, Tver, Russia