Introduction of Swarm Intelligent Algorithms

Abstract

AbstractIt is fairly accepted fact that one of the most important human activities is decision making. It does not matter what field of activity one belongs to. Whether it is political, military, economic or technological, decisions have a far reaching influence on our lives. Optimization techniques play an important role in structural design, the very purpose of which is to find the best ways so that a designer or a decision maker can derive a maximum benefit from the available resources. The methods of optimization can be divided into two category such as traditional optimization algorithms and modern optimization algorithms. The traditional optimization algorithms turn into an independent subject began in 1947 when Dantzig [1, 2] proposed the simplex method for solving general linear optimization problems. From then on, study on the optimization method is booming. Many methods of optimization are proposed [3] sequentially as follow: unconstrained optimization methods, large-scale unconstrained optimization methods, nonlinear least squares methods, linear constrained optimization methods, nonlinear constrained optimization methods and so on. These traditional mathematical gradient-based optimal techniques have been applied to the design of optimal structures [4]. While, many practical engineering optimal problems are very complex and hard to solve by traditional method [5].KeywordsGenetic AlgorithmParticle Swarm OptimiParticle Swarm Optimization AlgorithmHarmony SearchComputing ThinkingThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.