Comparing the Robustness of Evolutionary Algorithms on the Basis of Benchmark Functions

Advances in Electrical and Computer Engineering

卷:13

关键词: computational intelligence;    evolutionary computation;    heuristic algorithms;   

DOI  :  10.4316/AECE.2013.02010

来源: DOAJ

【 摘 要 】

In real-world optimization problems, even though the solution quality is of great importance, the robustnessof the solution is also an important aspect. This paper investigates how the optimization algorithms aresensitive to the variations of control parameters and to the random initialization of the solution set forfixed control parameters. The comparison is performed of three well-known evolutionary algorithms which areParticle Swarm Optimization (PSO) algorithm, Differential Evolution (DE) algorithm and the Harmony Search(HS) algorithm. Various benchmark functions with different characteristics are used for the evaluation ofthese algorithms. The experimental results show that the solution quality of the algorithms is not directlyrelated to their robustness. In particular, the algorithm that is highly robust can have a low solution quality,or the algorithm that has a high quality of solution can be quite sensitive to the parameter variations.

【 授权许可】

Unknown