Genetic Algorithm, Particle Swarm Optimization and Harmony Search: A Quick Comparison

被引：0
|
作者：
Sharma, Sonia [1 ]
Pandey, Hari Mohan [1 ]
机构：
[1] Am Univ Uttar Pradesh, Dept Comp Sci & Engn, Noida, India
来源：
2016 6TH INTERNATIONAL CONFERENCE - CLOUD SYSTEM AND BIG DATA ENGINEERING (CONFLUENCE) | 2016年
关键词：
algorithm; artificial intelligence; meta-heuristic algorithms; optimization; genetic algorithm; particle swarm optimization; harmony search;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
There exists several complex optimization problems, are difficult to solve using simple conventional or mathematical approach. Many scientific applications have a search space exponentially proportional to the problem dimensions, cannot be solved employing exhaustive search methods. Therefore, there is considerable interest in meta-heuristic methods attempt to discover near optimal solution within the acceptable time. This paper presents a comprehensive study and comparison of three: Genetic Algorithm, Particle Swarm Optimization and Harmony Search, global optimization algorithms. The comparative analysis has been reported in an organized manner for quick review. The underlying motivation is to identify possibility to develop a new hybrid algorithm to solve real world problems.
引用
收藏
页码：40 / 44
页数：5
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