Global optimization in large-scale distributed systems requires massive amounts of computations for complex objective functions. Conventional global optimization based on stochastic algorithms cannot guarantee an actual global optimum with a finite searching iteration. Therefore, scalability is a desirable feature for the optimization techniques in highly distributed dynamic environments, where...

Many optimization techniques have been proposed since the inception of engineering optimization in 1960s. Traditional mathematical modeling-based approaches are incompetent to solve the engineering optimization problems, as these problems have complex system that involves large number of design variables as well as equality or inequality constraints. In order to overcome the various difficultie...

Biogeography based optimization (BBO) is a type of evolutionary algorithm. It is a population based optimization algorithm and provides clarification about the changing distribution of all species in different environment with time. Biogeography-based Optimization (BBO) is a new intelligent optimization algorithm, which was developed by the simulation of the migration of biological organisms on...

introduction: diagnosis, prediction and control of oral lesions is usually done classically based on clinical signs and histopathologic features. due to lack of timely diagnosis in all conventional methods or differential diagnosis, biopsy of patient is needed. therefore, the patient might be irritated. so, an intelligent method for quick and accurate diagnosis would be crucial. intelligent sys...

The design, operation and control of stabilization -tracking systems has been a challenging task for the scientists and engineers with the present day requirements of modern aged sophistication of these systems. The conventional control concepts have been outplayed by the optimal control techniques with the evolution of the modern control theory. Moreover, due to the problems associated with mo...

Multi-objective optimization is widely applied in a number of areas now-a-days. Unfortunately, many combinatorial multi-objective optimization problems are NP-hard. However, it is often unnecessary to have an exact solution. So, heuristic approach can obtain a near-optimal solution in some reasonable time with the smallest possible computational burden. Intelligent Water Drops algorithm (IWD) a...

Artificial Bee Colony (ABC) algorithm which is one of the most recently introduced optimization algorithms, simulates the intelligent foraging behavior of a honey bee swarm. Clustering analysis, used in many disciplines and applications, is an important tool and a descriptive task seeking to identify homogeneous groups of objects based on the values of their attributes. In this work, ABC is use...

This paper presents a hybrid Proportional Integral Differential (PID) and Power System Stabilizer (PSS) controller based Artificial Bee Colony (ABC) techniques to damp low frequency oscillation. The recent studies in artificial intelligence demonstrated that the ABC optimization is strong intelligent method in complicated stability problems. The optimal PID and PSS parameters are applied on a S...

In this paper, an intelligent-gradient based algorithm is proposed to solve time optimal bang-bang control problem. The proposed algorithm is a combination of an intelligent algorithm called improved particle swarm optimization algorithm (IPSO) in the first stage of optimization process together with a gradient-based algorithm called successive quadratic programming method (SQP) in the second s...