RIOTS_95–a MATLAB Toolbox for Solving General Optimal Control Problems And Its Applications to Chemical Processes

RIOTS_95 is a group of programs and utilities, written mostly in C, Fortran and M-file scripts and designed as a toolbox for MATLAB, that provides an interactive environment for solving a very broad class of optimal control problems (OCP’s). RIOTS_95 comes pre-compiled for use with the Windows 95/98/2000 or Windows NT operating systems. The user’s … Read more

Nonlinear Optimisation in CHP-Applications

At the Fraunhofer Institute UMSICHT a nonlinear model has been developed facilitating the dynamic optimisation of combined heat and power production systems. The strategy called “dynamic supply temperature optimisation” is a very promising approach to use the DH-network itself as a large heat storage causing no additional investment cost. The pipeline system of a district … Read more

An Active-Set Algorithm for Nonlinear Programming Using Linear Programming and Equality Constrained Subproblems

This paper describes an active-set algorithm for large-scale nonlinear programming based on the successive linear programming method proposed by Fletcher and Sainz de la Maza. The step computation is performed in two stages. In the first stage a linear program is solved to estimate the active set at the solution. The linear program is obtained … Read more

A Primal-Dual Trust Region Algorithm for Nonlinear Optimization

This paper concerns general (nonconvex) nonlinear optimization when first and second derivatives of the objective and constraint functions are available. The proposed method is based on finding an approximate solution of a sequence of unconstrained subproblems parameterized by a scalar parameter. The objective function of each unconstrained subproblem is an augmented penalty-barrier function that involves … Read more

A Simple Primal-Dual Feasible Interior-Point Methodfor Nonlinear Programming with Monotone Descent

We propose and analyze a primal-dual interior point method of the “feasible” type, with the additional property that the objective function decreases at each iteration. A distinctive feature of the method is the use of different barrier parameter values for each constraint, with the purpose of better steering the constructed sequence away from non-KKT stationary … Read more

On the superlinear local convergence of a filter-SQP method

Transition to superlinear local convergence is shown for a modified version of the trust-region filter-SQP method for nonlinear programming introduced by Fletcher, Leyffer, and Toint [8]. Hereby, the original trust-region SQP-steps can be used without an additional second order correction. The main modification consists in using the Lagrangian function value instead of the objective function … Read more

Semidefinite optimization, a spectral approach

This thesis is about mathematical optimization. Mathematical optimization involves the construction of methods to solve optimization problems, which can arise from real-life problems in applied science, when they are mathematically modeled. Examples come from electrical design, engineering, control theory, telecommunication, environment, finance, and logistics. This thesis deals especially with semidefinite optimization problems. Semidefinite programming is … Read more

Symbolic-interval heuristic for bound-constrained minimization

Bound-constrained global optimization helps answer many practical questions in chemistry, molecular biology, economics. Most of algorithms for solution of global optimization problems are a combination of interval methods and exhuastive search. The efficiency of such algorithms is characterized by their ability to detect and eliminate sub-optimal feasible regions. This ability is increased by availability of … Read more

Computing Mountain Passes

We propose the elastic string algorithm for computing mountain passes in finite-dimensional problems. We analyze the convergence properties and numerical performance of this algorithm for benchmark problems in chemistry and discretizations of infinite-dimensional variational problems. We show that any limit point of the elastic string algorithm is a path that crosses a critical point at … Read more

Sufficient Global Optimality Conditions for Bivalent Quadratic Optimization

We prove a sufficient global optimality condition for quadratic optimization with quadratic constraints where the variables are allowed to take -1 and 1 values. We extend the condition to quadratic programs with matrix variables and orthogonality conditions, and in particular, to the quadratic assignment problem. CitationBilkent University Technical Report, September 2002.ArticleDownload View PDF