The programming of short-term financing

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A mixed-integer LP model for the optimal allocation of voltage regulators and capacitors in radial distribution systems

This paper presents a mixed-integer linear programming model to solve the problem of allocating voltage regulators and fixed or switched capacitors (VRCs) in radial distribution systems. The use of a mixed-integer linear model guarantees convergence to optimality using existing optimization software. In the proposed model, the steady-state operation of the radial distribution system is modeled through linear expressions. The results of one test system and one real distribution system are presented in order to show the accuracy as well as the efficiency of the proposed solution technique. An heuristic to obtain the Pareto front for the multiobjective VRCs allocation problem is also presented. © 2012 Elsevier Ltd. All rights reserved.

A mixed-integer linear programming approach for optimal type, size and allocation of distributed generation in radial distribution systems

This paper presents a mixed-integer linear programming approach to solving the problem of optimal type, size and allocation of distributed generators (DGs) in radial distribution systems. In the proposed formulation, (a) the steady-state operation of the radial distribution system, considering different load levels, is modeled through linear expressions; (b) different types of DGs are represented by their capability curves; (c) the short-circuit current capacity of the circuits is modeled through linear expressions; and (d) different topologies of the radial distribution system are considered. The objective function minimizes the annualized investment and operation costs. The use of a mixed-integer linear formulation guarantees convergence to optimality using existing optimization software. The results of one test system are presented in order to show the accuracy as well as the efficiency of the proposed solution technique.© 2012 Elsevier B.V. All rights reserved.

Rural development and urban food programming

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Sustainable urban energy planning: The case study of a tropical city

The urbanization of modern societies has imposed to the planners and decision-makers a more precise attention to facts not considered before. Several aspects, such as the energy availability and the deleterious effect of pollution on the populations, must be considered in the policy decisions of cities urbanization. The current paradigm presents centralized power stations supplying a city, and a combination of technologies may compose the energy mix of a country, such as thermal power plants, hydroelectric plants, wind systems and solar-based systems, with their corresponding emission pattern. A goal programming multi-objective optimization model is presented for the electric expansion analysis of a tropical city, and also a case study for the city of Guaratinguetá, Brazil, considering a particular wind and solar radiation patterns established according to actual data and modeled via the time series analysis method. Scenarios are proposed and the results of single environmental objective, single economic objective and goal programming multi-objective modeling are discussed. The consequences of each dispatch decision, which considers pollutant emission exportation to the neighborhood or the need of supplementing electricity by purchasing it from the public electric power grid, are discussed. The results revealed energetic dispatch for the alternatives studied and the optimum environmental and economic solution was obtained. © 2012 Elsevier Ltd.

programming by sectors and by regions, and preparation, presentation and evaluation of projects

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Multi-choice mixed integer goal programming optimization for real problems in a sugar and ethanol milling company

Goal Programming (GP) is an important analytical approach devised to solve many realworld problems. The first GP model is known as Weighted Goal Programming (WGP). However, Multi-Choice Aspirations Level (MCAL) problems cannot be solved by current GP techniques. In this paper, we propose a Multi-Choice Mixed Integer Goal Programming model (MCMI-GP) for the aggregate production planning of a Brazilian sugar and ethanol milling company. The MC-MIGP model was based on traditional selection and process methods for the design of lots, representing the production system of sugar, alcohol, molasses and derivatives. The research covers decisions on the agricultural and cutting stages, sugarcane loading and transportation by suppliers and, especially, energy cogeneration decisions; that is, the choice of production process, including storage stages and distribution. The MCMIGP allows decision-makers to set multiple aspiration levels for their problems in which the more/higher, the better and the less/lower, the better in the aspiration levels are addressed. An application of the proposed model for real problems in a Brazilian sugar and ethanol mill was conducted; producing interesting results that are herein reported and commented upon. Also, it was made a comparison between MCMI GP and WGP models using these real cases. © 2013 Elsevier Inc.

Estudio preliminar sobre la técnica de programación del desarrollo económico = Preliminary study of the technique of programming economic development

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Orientaciones metodológicas para la programación a corto plazo = Methodological principles for short-term programming

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