Conservation law constrained optimization based upon Front-Tracking

Conservation Law Constrained Optimization Based upon Front-tracking

We consider models based on conservation laws. For the optimization of such systems, a sensitivity analysis is essential to determine how changes in the decision variables influence the objective function. Here we study the sensitivity with respect to the initial data of objective functions that depend upon the solution of Riemann problems with piecewise linear flux functions. We present repres...

A Robust Knapsack Based Constrained Portfolio Optimization

Many portfolio optimization problems deal with allocation of assets which carry a relatively high market price. Therefore, it is necessary to determine the integer value of assets when we deal with portfolio optimization. In addition, one of the main concerns with most portfolio optimization is associated with the type of constraints considered in different models. In many cases, the resulted p...

A Conservation Law Method in Optimization

Abstract We propose some algorithms to find local minima in nonconvex optimization and to obtain global minima in some degree from the Newton Second Law without friction. With the key observation of the velocity observable and controllable in the motion, the algorithms simulate the Newton Second Law without friction based on symplectic Euler scheme. From the intuitive analysis of analytical sol...

A Conservative Front Tracking Method for Hyperbolic Conservation Laws

Motion tracking as a constrained optimization problem

In this paper we pose the problem of tracking of a varying number of points through an image sequence as a multi-objective optimization problem with additional hard constraints. One of the objectives is to 8nd smooth tracks based on second-order motion characteristics optimized over several frames. The corresponding optimization algorithm we present is a sequential heuristic search algorithm th...