A method has been developed for deriving the approximate global optimum of a nonlinear objective function. First, the objective function is expanded into a linear equation for a moment vector, and the optimization problem is reduced to an eigen analysis problem in the wave coefficient space. Next, the process of the optimization is expressed using a Schrödinger-type equation, so global optimiza...

Received Jan 14, 2017 Revised Mar 20, 2017 Accepted Apr 9, 2017 Meta-heuristics optimization is becoming a popular tool for solving numerous problems in real-world application due to the ability to overcome many shortcomings in traditional optimization. Despite of the good performance, there is limitation in some algorithms that deteriorates by certain degree of problem type. Therefore it is ne...

Sigmoid surface controller has been proved to be effective in motion control of autonomous underwater vehicles, but it is hard to adjust its control parameters. Improved particle swarm optimization of sigmoid surface controller was proposed in this paper, which solves the problems that particle swarm optimization may be trapped in local optimum and fails to converge to global optimum. Moreover,...

The particle swarm optimization (PSO) method is an instance of a successful application of the philosophy of bounded rationality and decentralized decision making for solving global optimization problems. A number of advantages with respect to other evolutionary algorithms are attributed to PSO making it a prospective candidate for optimum structural design. The PSO-based algorithm is robust an...

In this paper, an automatic control system design based on Integral Squared Error (ISE) parameter optimization technique has been implemented on longitudinal flight dynamics of an UAV. It has been aimed to minimize the error function between the reference signal and the output of the plant. In the following parts, objective function has been defined with respect to error dynamics. An unconstrai...

In this paper a fuzzy decision aid system is developed base on new concepts that presented in the field of fuzzy decision making in fuzzy environment (FDMFE). This framework aids decision makers to understand different circumstances of an uncertain problem that may occur in the future. Also, to keep decision maker from the optimization problem complexities, a decision support system, which can ...

The problem of obtaining sensitivity analysis information from optimization stochastic methods is addressed in this work. The sensitivity analysis calculation is obtained using the evaluations of the objective function as samples of the behavior of the objective function in the vicinity of the optimum. A linear optimization problem is formulated for the approximation of a contour surface of the...

in this paper, a new approach is proposed for the optimum design of single-phase induction motor. by using the classical design equations and the evolutionary algorithms such as genetic algorithms (ga), particle swarm optimization (pso) and modified particle swarm optimization (mpso), a single phase induction motor (spim) was designed with the maximum efficiency. the finite element method (fem)...

the main aim of this paper is to find the optimum shape of arch dams subjected to multiple natural frequency constraints by using an efficient methodology. the optimization is carried out by charged system search algorithm and its enhanced version. computing the natural frequencies by finite element analysis (fea) during the optimization process is time consuming. in order to reduce the computa...

land use optimization is one of the appropriate methods for soil conservation which helps decision makers and watershed planners in order to make the optimum decision among different land uses. the main objective of this research was to find the optimum area of each land use to reduce soil erosion rate as well as to increase the income of stakeholders in golroudbar watershed located in semnan p...