We propose a gradient-based method to solve quasiconvex optimization problems through decomposed optimization and prove local superlinear convergence under mild regularity assumptions at the optimal solution. A practical implementation further provides global convergence while maintaining the...

Globally optimal free flight trajectory optimization can be achieved with a combination of discrete and continuous optimization. A key requirement is that Newton's method for continuous optimization converges in a sufficiently large neighborhood around a minimizer. We show in this paper that,...

This article deals with practical problems of fitting empirical data with generalized lambda distribution. Given method based on moment matching is illustrated on a practical example.

This paper demonstrates how simple general equilibrium models can be solved with the help of Microsoft Excel. Two different general equilibrium models for tax incidence analysis are used as illustrative examples. The methods presented here are intended to be beneficial to both students and...

This article deals with practical problems of fitting empirical data with generalized lambda distribution. Given method based on moment matching is illustrated on a practical example.

In this paper we propose an accelerated version of the cubic regularization of Newton's method [6]. The original version, used for minimizing a convex function with Lipschitz-continuous Hessian, guarantees a global rate of convergence of order O(1/k exp.2), where k is the iteration counter. Our...