Using Echolocation Search Algorithm (ESA) for truss size optimization

Due to limited resources, and increasing speed of development, the optimal use of available resources has become the most important challenge of human societies. In the last few decades, many researchers have focused their research on solving various optimization problems, providing new optimization methods, and improving the performance of existing optimization methods. Echolocation Search Algorithm (ESA) is an evolutionary optimization algorithm that is based on mimicking the mechanism of the animals such as bats, dolphins, oilbirds, etc in food finding to solve optimization problems. In this paper, the ability of ESA for solving truss size optimization problems with continuous variables is investigated. To examine the efficiency of ESA, three benchmark examples are considered. The numerical results exhibit the effectiveness of ESA for solving truss optimization problems.