Estimate model parameter and the structure simultaneously is a crucial and challenging problem in system identification. For solving the problem, a hybrid algorithm by integrating two-order oscillating particle swarm optimization with successive quadratic programming is proposed in this paper. The two-order oscillating particle swarm optimization is showed to converge rapidly to a near optimum ...

The third-monthly (about 10 days in a time-step) hydropower scheduling, typically challenging nonlinear optimization, is one of the essential tasks power system with operational storage reservoirs. This work formulates problem into quadratic programming (QP), which solved successively, linearization updated on constraint firm yield from all cascaded Notably, generating discharge linearly concav...

in this paper, we deal to obtain some new complexity results for solving semidefinite optimization (sdo) problem by interior-point methods (ipms). we define a new proximity function for the sdo by a new kernel function. furthermore we formulate an algorithm for a primal dual interior-point method (ipm) for the sdo by using the proximity function and give its complexity analysis, and then we sho...

This paper addresses the problem of curtailing the number of control actions and minimizing controller movements for real-time voltagelreactive power control. Algorithms are proposed to identify the most effective subset of control actions and to minimize controller movements. An algorithmic objective function appropriate for the treatment of system security and economy is also proposed. It eli...

Quadratic programming (QP) is an optimization problem wherein one minimizes (or maximizes) a quadratic function of a finite number of decision variable subject to a finite number of linear inequality and/ or equality constraints. In this paper, a quadratic programming problem (FFQP) is considered in which all cost coefficients, constraints coefficients, and right hand side are characterized by ...

An efficient and numerically stable dual algorithm for positive definite quadratic programming is described which takes advantage of the fact lhat the unconstrained minimum of the objective function can be used as a starling point. Its implementation utilizes the Cholesky and QR factorizations and procedures for updating them. The performance of the dual algorithm is compared against that of pr...

The quadratic bilevel programming problem is an instance of a quadratic hierarchical decision process where the lower level constraint set is dependent on decisions taken at the upper level. By replacing the inner problem by its corresponding KKT optimality conditions, the problem is transformed to a single yet non-convex quadratic program, due to the complementarity condition. In this paper we...

in this paper, an integration of improve particle swarm optimization (ipso) incombination with successive quadratic programming (sqp) so called ipso-sqpalgorithm is proposed to solve time optimal bang-bang control problems. theprocedure is found not sensitive to the initial guess of the solution. due to randomselection in the first stage of the search process, the chance of converging to theglo...

This paper discusses an Interval Quadratic Programming (IQP) problem, where the constraints coefficients and the right-hand sides are represented by interval data. First, the focus is on a common method for solving Interval Linear Programming problem. Then the idea is extended to the IQP problem. Based on this method each IQP problem is reduced to two classical Quadratic Programming (QP) proble...

The paper deals with solving of contact problems with Coulomb friction for a system of 3D elastic bodies. The iterative method of successive approximations is used in order to find a fixed point of certain mapping that defines the solution. In each iterative step, an auxiliary problem with given friction is solved that is discretized by the FETI method. Then the duality theory of convex optimiz...