In this paper we extend the smoothing technique [7], [9] onto the problems of Semidefinite Optimization. For that, we develop a simple framework for estimating a Lipschitz constant for the gradient of some symmetric functions of eigenvalues of symmetric matrices. Using this technique, we can...

In this paper we outline the Lagrangian constrained optimization method to solve complex problems subject to constraints. Firstly we summarize the Lagrangian constrained optimization routine. Secondly we outline a detailed implementation strategy. Thirdly and finally we provide example and solve...

The rapid development of artificial intelligence methods contributes to their wide applications for forecasting various financial risks in recent years. This study introduces a novel explainable case-based reasoning (CBR) approach without a requirement of rich expertise in financial risk....

This paper intends to explore one of the relatively less highlighted area viz. interest rate risk management by Indian banks with a view to providing an innovative edge to the specific area in the Indian context. Firstly, the paper aims at building empirical relationships between the average...

The purpose of this study is to build a system that automatically generates an optimal strategy (AGOS) which can solve the business problem of maximizing the acceptance rate without taking more risks in loan approval process. This paper formulates the finding an optimal approval strategy of a...

Exporting countries are concerned that sanitary standards might shield domestic industry from foreign competition. This study analyzes economic effects of changes in Western Hemisphere sanitary requirements on broiler trade in the Americas. A mathematical programming model detects that if Brazil...

A divide and conquer algorithm for exploiting policy function monotonicity is proposed and analyzed. To solve a discrete problem with n states and n choices, the algorithm requires at most n log2(n) 5n objective function evaluations. In contrast, existing methods for non-concave problems require...

A divide and conquer algorithm for exploiting policy function monotonicity is proposed and analyzed. To solve a discrete problem with n states and n choices, the algorithm requires at most nlog2(n)+5n objective function evaluations. In contrast, existing methods for nonconcave problems require...