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 ...

Start working toward program admission and requirements right away. Work you complete in the non-credit experience will transfer to the for-credit experience when you ...

CBSE 2025 Competency-Based Questions: The Central Board of Secondary Education (CBSE) has officially released the practice question paper for the academic year 2024-25, for the class 12th on its ...

In this paper, we introduce an approach for constructing uncertainty sets for robust optimization using new deviation measures for random variables termed the forward and backward deviations. These ...

A thorough understanding of Linear Algebra and Vector Calculus, and strong familiarity with the Python programming language (e.g., basic data manipulation libraries, how to construct functions and ...

Roughly, we will cover the following topics (some of them may be skipped depending on the time available). Linear Programming: Basics, Simplex Algorithm, and Duality. Applications of Linear ...

A framework based on advanced AI techniques can solve complex, computationally intensive problems faster and in a more more scalable way than state-of-the-art methods, according to a new study. A ...

Genetic programming (GP) represents a class of evolutionary algorithms that automates the creation of computer programmes to solve complex problems. Coupled with symbolic regression (SR), which aims ...