‎in this paper we introduce a numerical approach that solves optimal control problems (ocps)‎‎using collocation methods‎. ‎this approach is based upon b-spline functions‎.‎the derivative matrices between any two families of b-spline functions are utilized to‎‎reduce the solution of ocps to the solution of nonlinear optimization problems‎.‎numerical experiments confirm our theoretical findings‎.

This paper presents an overview of the recent advances in deterministic global optimization approaches and their applications in the areas of Process Design and Control. The focus is on global optimization methods for (a) twice-diierentiable constrained nonlinear optimization problems, (b) mixed-integer nonlinear optimization problems, and (c) locating all solutions of nonlinear systems of equa...

In this paper particle swarm optimization(PSO)has been applied for the design of the optimal robust controllers for third order systems . The controller design problem is posed as constrained nonlinear optimization problem. The parameters of the chosen controller are obtained solving the nonlinear constrained optimization problem.The performance index which has been used in the design is integr...

optimization of maintenance resources to maximize the system availability is a major concern in different manufacturing systems. therefore, a lot of effort is put to construct optimization models to reach the maximum availability level and to reduce the costs of lack of availability. however, despite these efforts, data uncertainty in the real world problems was neglected in proposed models whi...

This paper considers the nonlinear systems modeling problem for control. A structured nonlinear parameter optimization method (SNPOM) adapted to radial basis function (RBF) networks and an RBF network-style coefficients autoregressive model with exogenous variable model parameter estimation is presented. This is an off-line nonlinear model parameter optimization method, depending partly on the ...

Financial applications have a long history of including optimization, starting with Markowitz’s origin of the quadratic optimization model for determining an efficient portfolio to minimize variance for a given return. Portfolio optimization continues to be an active area with most applications focused on linear and quadratic optimization. General nonlinear optimization arises in this area, how...

This paper presents an overview of the research progress in global optimization during the last 5 years (1998–2003), and a brief account of our recent research contributions. The review part covers the areas of (a) twice continuously differentiable nonlinear optimization, (b) mixedinteger nonlinear optimization, (c) optimization with differential-algebraic models, (d) optimization with grey-box...

abstract. when a production facility is designed, there are various parameters affecting the number machines such as production capacity and reliability. it is often a tedious task to optimize different objectives simultaneously. the other issue is the uncertainty in many design parameters which makes it difficult to reach a desirable solution. in this paper, we present a new mathematical model...

Linear programming problem is widely applied in engineering group. And artificial neural network is an effective and practical method and approach for solving linear programming problem of nonlinear convex set constraints in engineering field. Most models of artificial neural network are nonlinear dynamic system. If the objective function of optimization calculation problem is corresponding to ...