A Study on the Effect of Local Neighbourhood Parameter towards the Performance of SAFIRO - Ab Rahman, Tasiransurini; Ibrahim, Zuwairie; Azlina Ab. Aziz, Nor; Hidayati Abdul Aziz, Nor; Khairi Mohammed, Suad; Muhammad, Badaruddin; Md Yussof, Zulkifli (International Journal of Engineering and Technology, 2018)
Single-agent Finite Impulse Response Optimizer (SAFIRO) is a recently proposed metaheuristic optimization algorithm which adopted the procedure of the ultimate unbiased finite impulse response filter (UFIR) in state estimation. In SAFIRO, a random mutation with shrinking local neighborhood method is employed during measurement phase to balance the exploration and the exploitation process. Beta, Î², is one of the parameters used in the local neighborhood to control the step size. In this study, the effect of Î² towards the performance of SAFIRO is observed by assigning the value of 1, 5, 10, 15, and 20. The best setting of Î² for SAFIRO is also determined. The CEC2014 Benchmark Test Suite is used to evaluate the SAFIRO performance with different Î² values. Results show that the performance of Î² is depending on the problems to be optimized. 17 out of 30 functions show the best performance of SAFIRO by setting Î² = 10. Statistical analysis using Friedman test and Holm post hoc test were performed to rank the performance. Î² = 10 has the highest rank where its performance is significantly better than other values, but equivalent to Î² = 5 and Î² = 15. Hence, it is recommended to tune the Î² for best performance, however, Î² = 10 is a good value to be used in SAFIRO for solving optimization problems.Â Â