A metaheuristic is generally a procedure designed to find a good solution to a difficult optimization problem. Known optimization search metaheuristics heavily rely on parameters, which are usually introduced so that the metaheuristic follows some supposedly related to the optimization problem natural process (simulated annealing, swarm optimization, genetic algorithms). Adjusting the parameter...

In the paper a linear-quadratic optimization problem (LCTOR) with unseparated two-point boundary conditions is considered. To solve this problem is proposed a new sweep algorithm which increases doubles the dimension of the original system. In contrast to the well-known methods, here it refuses to solve linear matrix and nonlinear Riccati equations, since the solution of such multi-point optimi...

In this paper, a special class of redundancy optimization problem with fuzzy random variables is presented. In this model, fuzzy random lifetimes are considered as basic parameters and the Er-expected of system lifetime is used as a major type of system performance. Then a redundancy optimization problem is formulated as a binary integer programming model. Furthermore, illustrative numerical ex...

In this study, a new method for designing the damping controller was proposed to improve the transient power system stability in a single machine network connected to an infinite bus. The STATCOM controller problem in a wide area of the system function was considered as an optimization problem with multi-purpose objective function. Also, the Honey Bee Mating Optimization Algorithm was used to d...

In this study, the finite element model updating was simulated by reducing the stiffness of the members. Due to lack of access to the experimental results, the data obtained from an analytical model were used in the proposed structural damage scenarios. The updating parameters for the studied structures were defined as a reduction coefficient applied to the stiffness of the members. Parameter v...

location-allocation is a combinatorial optimization problem, and is defined as non deterministic polynomial hard (np) hard optimization. therefore, solution of such a problem should be shifted from exact to heuristic or meta heuristic due to the complexity of the problem. locating medical centers and allocating injuries of an earthquake to them has high importance in earthquake disaster managem...

this study proposes a combination of a fuzzy sliding mode controller (fsmc) with integral-proportion-derivative switching surface based superconducting magnetic energy storage (smes) and pid tuned by a multi-objective optimization algorithm to solve the load frequency control in power systems. the goal of design is to improve the dynamic response of power systems after load demand changes. in t...

knowing the fact that the main weakness of the most standard methods including k-means and hierarchical data clustering is their sensitivity to initialization and trapping to local minima, this paper proposes a modification of convex data clustering  in which there is no need to  be peculiar about how to select initial values. due to properly converting the task of optimization to an equivalent...

in this paper, a novel compensator based on magnetically controlled reactor with fixed capacitor banks (fc-mcr) is introduced and then power system stability in presence of this compensator is studied using an intelligent control method. the problem of robust fc-mcr-based damping controller design is formulated as a multi-objective optimization problem. the multi-objective problem is concocted ...

this article is devoted to the simultaneous optimization of shape and topology of shell structures. the optimum shape is obtained together with the optimum layout for the reinforcement layers at the both sides of the shell surface. to solve this problem the finite element method is employed. it is assumed that each element is comprised of a porous media with microscopic rectangular voids where ...