Hydrology of the Upper Ganga River

River basins / Flow / Hydrology / Models / Runoff / India / Nepal / Tibet / Bangladesh / Upper Ganga River

The implementation of the Tsunami Livelihood Restoration Project: Progress report 2005

Natural disasters / Rehabilitation / Living conditions / Farmers’ associations / Sri Lanka / Hambantota District

Optimal Fleet Size of an Integrated Production and Distribution Scheduling Problem for a Single Perishable Product

This dissertation focuses on a practical production problem in which a perishable product must be produced and distributed at minimum cost. The problem has some features of the integrated production and distribution scheduling problem in that we seek to determine the fleet size and their routes subject to a planning horizon constraint but there are significant differences as well. In particular, this research differs because the product has a limited lifetime, the total demand must be satisfied within a planning horizon, multiple trucks can be used, and the production schedule and the distribution sequence are considered. Two mixed integer programming models are formulated to solve the single plant and two-plant problems and, then, heuristics based on evolutionary algorithms are provided to resolve the models in a reasonable tim

A geometric view on Pearson’s correlation coefficient and a generalization of it to non-linear dependencies

Measuring strength or degree of statistical dependence between two random variables is a common problem in many domains. Pearson’s correlation coefficient ρ is an accurate measure of linear dependence. We show that ρ is a normalized, Euclidean type distance between joint probability distribution of the two random variables and that when their independence is assumed while keeping their marginal distributions. And the normalizing constant is the geometric mean of two maximal distances; each between the joint probability distribution when the full linear dependence is assumed while preserving respective marginal distribution and that when the independence is assumed. Usage of it is restricted to linear dependence because it is based on Euclidean type distances that are generally not metrics and considered full dependence is linear. Therefore, we argue that if a suitable distance metric is used while considering all possible maximal dependences then it can measure any non-linear dependence. But then, one must define all the full dependences. Hellinger distance that is a metric can be used as the distance measure between probability distributions and obtain a generalization of ρ for the discrete case