Sets and indices in linear programming modelling and their integration with relational data models

LP models are usually constructed using index sets and data tables which are closely related to the attributes and relations of relational database (RDB) systems. We extend the syntax of MPL, an existing LP modelling language, in order to connect it to a given RDB system. This approach reuses existing modelling and database software, provides a rich modelling environment and achieves model and data independence. This integrated software enables Mathematical Programming to be widely used as a decision support tool by unlocking the data residing in corporate databases

Introducing new constructs for data modelling and column generation in LP modelling languages

Through popular implementation of structured query language (SQL) and query-by-example(QBE) relational databases have become the de-facto industry standard for data modelling.We consider the indices, sets, and the declarative form of Linear Programming (LP) modelling languages and introduce new constructs which provide direct link to the database systems. The models constructed in this way are data driven and display a dynamicstructure. We then show how this approach can be naturally extended to include column generation features stated in procedural forms within an otherwise declarative modelling paradigm

A spectral deferred correction strategy for low Mach number reacting flows subject to electric fields

We propose an algorithm for low Mach number reacting flows subjected to electric field that includes the chemical production and transport of charged species. This work is an extension of a multi-implicit spectral deferred correction (MISDC) algorithm designed to advance the conservation equations in time at scales associated with advective transport. The fast and nontrivial interactions of electrons with the electric field are treated implicitly using a Jacobian-Free Newton Krylov approach for which a preconditioning strategy is developed. Within the MISDC framework, this enables a close and stable coupling of diffusion, reactions and dielectric relaxation terms with advective transport and is shown to exhibit second-order convergence in space and time. The algorithm is then applied to a series of steady and unsteady problems to demonstrate its capability and stability. Although developed in a one-dimensional case, the algorithmic ingredients are carefully designed to be amenable to multidimensional applications

Small manufacturing plants, pollution, and poverty : new evidence from Brazil and Mexico

The authors use new data from Brazil and Mexico to analyze relationships linking economic development, the size distribution of manufacturing plants, and exposure to industrial pollution. For lack of data, prior work in this field has been limited largely to water pollution and medium-size plants. This study examines air pollution and encompasses small plants (with 1 to 20 employees) as well as medium-size and large plants. Four main questions are addressed (with answers from plant-level data): a) Are small plants more pollution-intensive than large facilities? Clearly, yes. b) Are there proportionately more small plants in low-income regions? The answer is yes, in thousands of Brazilian municipalities. Small plants dominate poor regions and are a relatively low source of employment in high-income areas. c) Is industry more pollution-intensive in low-income regions? In Brazil, yes. For each municipality, the authors estimate the share of the six most pollution-intensive ("dirty") sectors in total industrial activity. They find that the dirty-sector share declines continuously with increases in municipality income per capita. d) Do poor areas suffer more than wealthy areas from industrial air pollution? Paradoxically, no. The risk of mortality from industrial air pollution is much higher in the top two income deciles among Brazil's municipalities and the great majority of projected deaths is attributable to emissions from large plants.The scale of large-plant emissions dominates all other factors. Lower-income areas suffer much less from industrial air pollution in Brazil, despite the greater emissions-intensity of smaller plants and the prevalence of smaller plants in lower income areas.Water and Industry,Environmental Economics&Policies,Sanitation and Sewerage,Public Health Promotion,Health Monitoring&Evaluation,Environmental Economics&Policies,Water and Industry,Health Monitoring&Evaluation,Sanitation and Sewerage,TF030632-DANISH CTF - FY05 (DAC PART COUNTRIES GNP PER CAPITA BELOW USD 2,500/AL