An Implementation of Tree-Seed Algorithm (TSA) for Constrained Optimization

Abstract

One of the recent proposed population-based heuristic search algorithms is tree-seed optimization algorithm, TSA for short. TSA simulates the growing over on a land of trees and seeds and it has been proposed for solving unconstrained continuous optimization problems. The trees and their seeds on the D-dimensional solution space correspond to the possible solution for the optimization problem. At the beginning of the search, the trees are sowed to the land, and a number of seeds for each tree are produced during the iterations. The tree is removed from the stand and its best seed is added to the stand if the fitness of the best seed is better than the fitness of this tree. In the present study, a constraint optimization problem, the well-known pressure vessel design-PVD problem, is solved by using TSA. To overcome the constraints of the problem, a penalty function is used and the problem is considered as a single objective optimization problem. The experimental results obtained by the TSA are compared with the results of state-of-art methods such as artificial bee colony (ABC) and particle swarm optimization (PSO). Based on the solution quality and robustness, the promising and comparable results are obtained by the proposed approach.