DUAL SEARCH FIREFLY ALGORITHM FOR FUNCTION OPTIMIZATION
Journal Title: Advance Research Journal of Multidisciplinary Discoveries - Year 2018, Vol 31, Issue 31
Abstract
Accurate forecast of the micrometric precision of function value are extremely important in the optimization process. It reduces operation cost and gives accurate control of process quality. Due to the uncertain characteristics of the complicated function, many research studies have moved to nonlinear forecasting methods. One of the forecasting methods used in the mentioned issue is firefly algorithm (FA).The FA is a meta-heuristic algorithm that has been successfully applied in many practical applications. However, the FA had a few disadvantages in global searching including slow convergence speed, high possibility of being trapped in local optimum and low solution accuracy. Therefore, this paper proposed an improved FA known as dual search firefly algorithm (DSFA), for solving the function optimization problems. The DSFA employed the characteristics of speedy local search approach with the global optimization of FA. The experimental results showed that the proposed algorithm has overall improved over 85% in performances compared to FA in terms of convergence speed and accuracy.
Authors and Affiliations
Lim Eng Aik, Tan Wei Hong, Ahmad Kadri Junoh
Keywords
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