The design of linear Support Vector Machine (SVM) classification techniques is generally a Multi-objective Optimization Problem (MOP). These require finding appropriate trade-offs between two objectives, such as the amount misclassified training data (classification error) and number non-zero elements separator hyperplane. In this article, we review several SVM models in form multi-objective op...

A wide spectrum of “real world” problems, such as vehicle routing, machine and crew scheduling, facility location, portfolio analysis, electricity generation planning, and communication and transportation network design, demands the use of combinatorial optimization methods. By a combinatorial optimization problem, we mean a program where a linear or nonlinear objective function must be optimiz...

optimization of the exploitation operation is one of the most important issues facing the mining engineers. since several technical and economic parameters depend on the cut-off grade, optimization of this parameter is of particular importance. the aim of this optimization is to maximize the net present value (npv). since the objective function of this problem is non-linear, three methods can b...

in this paper, a multi-objective method is used to optimize a heat recovery steam generator (hrsg). two objective functions have been used in the optimization, which are irreversibility and hrsg equivalent volume. the former expresses the exergetic efficiency and the latter demonstrates the cost of the hrsg. decision variables are geometric and operational parameters of the hrsg. the results of...

This paper is comprised of the modeling and optimization of a multi objective linear programming problem in fuzzy environment in which some goals are fractional and some are linear. Here, we present a new approach for its solution by using α-cut of fuzzy numbers. In this proposed method, we first define membership function for goals by introducing non-deviational variables for each of objective...

Article history: Received: 19.06.2014. Received in revised form: 06.11.2014. Accepted: 11.11.2014. This paper addresses the robust model predictive control (MPC) for a class of time delay descriptor systems with linear fractional uncertainty and input constrains. The systems are transferred to the piecewise continuous descriptor systems and a piecewise constant control sequence is calculated by...

Optimization algorithms are routinely used to find the minimum or maximum solution corresponding to one or more objective functions, subject to satisfying certain constraints. However, monotonicity analysis is a process which, in certain problems, can instantly bring out important properties among decision variables corresponding to optimal solutions. As the name suggests, the objective functio...

wind power has been widely considered and utilized in recent years as one of the most promising renewable energy sources. in the current research study, aerodynamic analysis of the upwind three-bladed horizontal axis turbine is carried out using blade element momentum theory (bem), and a genetic algorithm (ga) is applied as an optimization method. output power generation is considered as an obj...