Universiti Teknologi Malaysia Institutional Repository

Performance of different techniques applied in genetic algorithm towards benchmark functions

Lim, S. P. and Haron, H. (2013) Performance of different techniques applied in genetic algorithm towards benchmark functions. In: Lecture Notes In Computer Science (Including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics).

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Official URL: https://doi.org/10.1007/978-3-642-36546-1_27

Abstract

Optimisation is the most interesting problems to be tested by using Artificial Intelligence (AI) methods because different optimal results will be obtained when different methods are implemented. Yet, there is no exact solution from the methods implemented because random function is usually applied. Genetic algorithm is a popular method which is used to solve the optimisation problems. However, no any methods can execute perfectly because the way of the method performs is different. Therefore, this paper proposed to compare the performance of GA with different operation techniques by using the benchmark functions. This can prove that different techniques applied in the operations can let GA produces different result. Based on the experiment result, GA is proved to perform well in the optimisation problems but it highly depends on the techniques implemented. The techniques for each operation have shown different performance in obtaining the time, minimum and average values for benchmark functions.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:algorithm
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computing
ID Code:51240
Deposited By: Haliza Zainal
Deposited On:27 Jan 2016 01:53
Last Modified:13 Sep 2017 08:02

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