A METAHEURISTIC OPTIMIZATION ALGORITHM INSPIRED BY TREE PHYSIOLOGICAL SYSTEM

The main disadvantage of metaheuristic algorithm is no guarantee that a global optimum solution due to the stochastic characteristic driven by the mechanism of exploration and exploitation. These components need to be balanced in order to improve the algorithm performance with smaller variance of solution under repetitive trials, faster convergence towards global optimum and thus with lesser computation cost. There are several factors that affecting the tradeoff between both components. These include randomization mechanism, application of support parameters, fitness assignment, and search dynamic