Efficiency of Maximum Likelihood Estimators under Different Censored Sampling Schemes for Rayleigh Distribution

The objective of this article is to study the effect of different types of censored sampling schemes on the estimation of the unknown parameter for Rayleigh distribution. The censored sampling schemes namely; type-I, type-II and progressive type-II censored sampling are to be considered. The comparisons made between the samples are based on the Fisher information, … Read more

Approximate Primal Solutions and Rate Analysis in Dual Subgradient Methods

We study primal solutions obtained as a by-product of subgradient methods when solving the Lagrangian dual of a primal convex constrained optimization problem (possibly nonsmooth). The existing literature on the use of subgradient methods for generating primal optimal solutions is limited to the methods producing such solutions only asymptotically (i.e., in the limit as the … Read more

A new method for solving linear fractional programming problems

In this paper a new method is suggested for solving the problem in which the objective function is a linear fractional function, and where the constraint functions are in the form of linear inequalities. The proposed method is based mainly upon solving this problem algebraically using the concept of duality. Since the earlier methods based … Read more

An estimation-free, robust conditional value-at-risk portfolio allocation model

We propose a novel optimization model for risk-averse investors to obtain robust solutions for portfolio allocation problems. Unlike related models in the literature, no historical data or statistical estimation techniques are used to compute the parameters of the model. Instead, the parameters are directly obtained from current prices of options on the assets being considered. … Read more

A strengthened formulation for the open pit mine production scheduling problem

We present a strengthened integer programming formulation for the open pit mine production scheduling problem, where the precedence and production constraints are combined to form 0-1 knapsack inequalities. Addition of corresponding knapsack cover inequalities decreases the computational requirements to obtain the optimal integer solution, in many cases by a significant margin. Citation The University of … Read more

Derivative Free Optimization Methods for Optimizing Stirrer Configurations

In this paper a numerical approach for the optimization of stirrer configurations is presented. The methodology is based on a flow solver, and a mathematical optimization tool, which are integrated into an automated procedure. The flow solver is based on the discretization of the incompressible Navier-Stokes equations by means of a fully conservative finite-volume method … Read more

Survey of Derivative Free Optimization Methods based on Interpolation

In this survey article we give the basic description of the interpolation based derivative free optimization methods and their variants. We review the recent contributions dealing with the maintaining the geometry of the interpolation set, the management of the trust region radius and the stopping criteria. Derivative free algorithms developed for problems with some structure … Read more


The central objective of this paper is to develop a transparent, consistent, self-contained, and stable country risk rating model, closely approximating the country risk ratings provided by Standard and Poor’s (S&P). The models should be non-recursive, i.e., they should not rely on the previous years’ S&P ratings. The selected set of variables includes not only … Read more

The Variational Inequality Approach for Solving Spatial Auction Problems with Joint Constraints

We consider a problem of managing a system of spatially distributed markets under capacity and balance constraints and show that solutions of a variational inequality enjoy auction principle properties implicitly. This enables us to develop efficient tools both for derivation of existence and uniqueness results and for creation of solution methods. Citation Kazan University, Kazan, … Read more

A novel elitist multiobjective optimization algorithm: multiobjective extremal optimization

Recently, a general-purpose local-search heuristic method called Extremal Optimization (EO) has been successfully applied to some NP-hard combinatorial optimization problems. This paper presents an investigation on EO with its application in multiobjective optimization and proposes a new novel elitist multiobjective algorithm, called Multiobjective Extremal Optimization (MOEO). In order to extend EO to solve the multiobjective … Read more