Estimation errors or uncertainities in expected return and risk measures create difficulties for portfolio optimization. The literature deals with the uncertainty using stochastic, fuzzy or ...

DUBLIN--(BUSINESS WIRE)--Research and Markets(http://www.researchandmarkets.com/research/799091/deterministic_oper) has announced the addition of John Wiley and Sons ...

Deciding how best to use limited resources is a universal issue that spares no individual or business. In today’s competitive quarter-to quarter environment, it’s critically important to your ...

An optimization problem is one where you have to make the best decision (choose the best investments, minimize your company’s costs, find the class schedule with the fewest morning classes, or so on).

We address the Least Quantile of Squares (LQS) (and in particular the Least Median of Squares) regression problem using modern optimization methods. We propose a Mixed Integer Optimization (MIO) ...

Students will learn the foundations of linear programming, properties of optimal solutions and various solution methods for optimizing problems involving a linear objective function and linear ...

There are three groups of optimization techniques available in PROC NLP. A particular optimizer can be selected with the TECH=name option in the PROC NLP statement. Since no single optimization ...

Combinatorial optimisation is a fundamental field in applied mathematics and computer science that focuses on finding an optimal object from a finite set of objects. In this context, problems are ...

There was an error while loading. Please reload this page. Linear programming (also called linear optimization) is a mathematical framework that represents an ...