The Complexity of Flow Expansion and Electrical Flow Expansion

FlowExpansion is a network design problem, in which the input consists of a flow network and a set of candidate edges, which may be added to the network. Adding a candidate incurs given costs. The goal is to determine the cheapest set of candidate edges that, if added, allow the demands to be satisfied. FlowExpansion is a variant of the Minimum-Cost Flow problem with non-linear edge costs. We study FlowExpansion for both graph-theoretical and electrical flow networks. In the latter case this problem is also known as the Transmission Network Expansion Planning problem. We give a structured view over the complexity of the variants of FlowExpansion that arise from restricting, e.g., the graph classes, the capacities, or the number of sources and sinks. Our goal is to determine which restrictions have a crucial impact on the computational complexity. The results in this paper range from polynomial-time algorithms for the more restricted variants over NP-hardness proofs to proofs that certain variants are NP-hard to approximate even within a logarithmic factor of the optimal solution

Large-scale unit commitment under uncertainty: an updated literature survey

The Unit Commitment problem in energy management aims at finding the optimal production schedule of a set of generation units, while meeting various system-wide constraints. It has always been a large-scale, non-convex, difficult problem, especially in view of the fact that, due to operational requirements, it has to be solved in an unreasonably small time for its size. Recently, growing renewable energy shares have strongly increased the level of uncertainty in the system, making the (ideal) Unit Commitment model a large-scale, non-convex and uncertain (stochastic, robust, chance-constrained) program. We provide a survey of the literature on methods for the Uncertain Unit Commitment problem, in all its variants. We start with a review of the main contributions on solution methods for the deterministic versions of the problem, focussing on those based on mathematical programming techniques that are more relevant for the uncertain versions of the problem. We then present and categorize the approaches to the latter, while providing entry points to the relevant literature on optimization under uncertainty. This is an updated version of the paper "Large-scale Unit Commitment under uncertainty: a literature survey" that appeared in 4OR 13(2), 115--171 (2015); this version has over 170 more citations, most of which appeared in the last three years, proving how fast the literature on uncertain Unit Commitment evolves, and therefore the interest in this subject

Data for: Incorporating Black-Litterman Views in Portfolio Construction when Stock Returns are a Mixture of Normals

This spreadsheet contains the raw data used in the numerical experiments of the paper "Incorporating Black-Litterman Views in Portfolio Construction when Stock Returns are a Mixture of Normals". It contains two 360x11 matrices representing the return and percentage market capitalization for the 11 sectors in S&P 500 index over a period of 360 months

Data for: Incorporating Black-Litterman Views in Portfolio Construction when Stock Returns are a Mixture of Normals

This spreadsheet contains the raw data used in the numerical experiments of the paper "Incorporating Black-Litterman Views in Portfolio Construction when Stock Returns are a Mixture of Normals". It contains two 360x11 matrices representing the return and percentage market capitalization for the 11 sectors in S&P 500 index over a period of 360 months.THIS DATASET IS ARCHIVED AT DANS/EASY, BUT NOT ACCESSIBLE HERE. TO VIEW A LIST OF FILES AND ACCESS THE FILES IN THIS DATASET CLICK ON THE DOI-LINK ABOV

Diverse glial cell line-derived neurotrophic factor (GDNF) support between mania and schizophrenia: A comparative study in four major psychiatric disorders

Background: Brain-derived neurotrophic factor (BDNF) and glial cell line-derived neurotrophic factor (GDNF) have essential roles in synaptic plasticity which is involved in pathogenesis and treatment of psychiatric disorders. However, it is not clear whether they act simultaneously during illness states in major psychiatric disorders