Abstract: System entropy describes the dispersal of a system’s energy and is an indication of the disorder of a physical system. Several system entropy measurement methods have been developed for dynamic systems. However, most real physical systems are always modeled using stochastic partial differential dynamic equations in the spatio-temporal domain. No efficient method currently exists that ...

In this paper, we propose two techniques to solve the nonlinear constrained optimization problem in large scale mesh-interconnected system. The first one is a diagram-method-based decomposition technique which decomposes the large scale system into some small subsystems. The second technique is a projected-Jacobi-based parallel dual-type method which can solve the optimization problems in the d...

Distributed power control by beamforming approach in cognitive radio networks requires a precise analysis of the impacts of the transmission parameters, tolerable interference and guarantees the quality of service of both the primary users and secondary users. In this paper, we propose an improved performance to solve the constrained nonlinear multi-object optimization and coherent power assign...

An algorithm is presented for solving nonlinear optimization problems with chance 5 constraints, i.e., those in which a constraint involving an uncertain parameter must be satisfied with at 6 least a minimum probability. In particular, the algorithm is designed to solve cardinality-constrained 7 nonlinear optimization problems that arise in sample average approximations of chance-constrained 8 ...

A method for simultaneously constructing a reduced-order model and using it as a surrogate model to solve a PDE-constrained optimization problem is introduced. A reducedorder model is built for the parameters corresponding to the initial guess of the optimization problem. Since the resulting reduced-order model can be expected to be accurate only in the vicinity of this point in the parameter s...

The main purpose of this paper is to describe the design, implementation and possibilities of our object-oriented library of algorithms for dynamic optimization problems. We briefly present library classes for the formulation and manipulation of dynamic optimization problems, and give a general survey of solver classes for unconstrained and constrained optimization. We also demonstrate methods ...

Discrete, nonlinear and PDE constrained optimization are mostly considered as different fields of mathematical research. Nevertheless many real-life problems are most naturally modeled as PDE constrained mixed integer nonlinear programs. For example, nonlinear network flow problems where the flow dynamics are governed by a transport equation are of this type. We present four different applicati...