The New Meta-heuristic Optimization Method: Optimizing Triangle Algorithm (OTA)

Heuristic optimization is an effective method for solving difficult problems in almost all areas of practical engineering issues, which in most cases do not have analytical solutions. In this paper, a new meta-heuristic optimization method, inspired by the triangle geometry, is presented, named as the Optimizing Triangle Algorithm (OTA) . In this method, the initial vector consist of all design variables (initial population) is considered as the base of the triangle (or the first row). The objective functions are worked out and the best and worst responses are calculated. The worst response along with its variables are omitted from the population. By recovery, rest of population forms the second row of the triangle. This process continues until the triangle apex or the optimal answer is acquired. In the second iteration, a certain number of initial populations of design variables are produced around the optimum point of previous triangle. The rest of population is created in initial range of each design variable, in order to escape from the local optimums. By this manner, the base of the second optimal triangle is formed. Subsequently, similar to the previous stage, computations are repeated to obtain the optimal response of the second triangle. These operations are continued to meet the convergence condition. To illustrate the capabilities of the proposed algorithm, some standard functions were selected to optimize. The achieved results were compared to the analytical solutions as well as other method used in reference. The optimum results of the test functions obtained by the OTA, well illustrate the ability of the OTA in solving the optimization problems.

Keywords:

Optimization , Meta-heuristic , Algorithm , Test Function