A Comparison of Optimization Problems for Planthopper Algorithm

Abstract

In this research, we discuss the planthopper algorithm (PA) as an algorithm for finding the optimal values. The

proposed algorithm is inspired by the food searching habit of the planthopper.  To evaluate the proposed algorithm, we tested on optimization of benchmark mathematic functions, comparing to the Cuckoo Search Algorithm, Bat Algorithm and Fruit Fly Algorithm. Those algorithms have limitations on the speed of convergence into solutions and the determination of parameters as constant. In the problem of finding the minimum of 4 mathematical functions, the function is the Sphere function, Griewank function, Rosenbrock function and Ackley function. The Planthopper algorithm gives the best average fitness in the Griewank function (=0.00012, S.D.= 0.00191) and the Ackley function (=0.03102, S.D.= 0.16076). The results showed that the proposed algorithm could solve the optimization problems comparable to other existing algorithms, even better in some problems.