Hybrid Improved Dolphin Echolocation and Ant Colony Optimization for Optimal Discrete Sizing of Truss Structures

Abstract

This paper presents a robust hybrid improved dolphin echolocation and ant colony optimization algorithm (IDEACO) for optimizing the truss structures with discrete sizing variables. The dolphin echolocation (DE) is inspired by the navigation and hunting behavior of dolphins. An improved version of dolphin echolocation (IDE), as the main engine, is proposed and uses the positive attributes of ant colony optimization (ACO) to increase the efficiency of the IDE. Here, ACO is employed to improve the precision of the global optimization solution. In the proposed hybrid optimization method, the balance between exploration and exploitation process was the main factor to control the performance of the algorithm. IDEACO algorithm performance is tested on several problems of benchmarks discrete truss structure optimization. The results indicate the excellent performance of the proposed algorithm in optimum design and rate of convergence in comparison with other metaheuristic optimization methods, so IDEACO offers a good degree of competitiveness against other existing metaheuristic methods.