We present an opportunity to use a combination of computer based tools for generating risk functions, simulation, classical decision rules and linearprogramming (LP) as tools for decision making. This new approach is...
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We present an opportunity to use a combination of computer based tools for generating risk functions, simulation, classical decision rules and linearprogramming (LP) as tools for decision making. This new approach is demonstrated by the use of an example which addresses the optimal assemblage of a pig fattening enterprise, whereby some basic data (e.g. prices, labour costs and average daily weight increases) are risk functions. Some coefficients, especially in the objective function (maximum gross margin) are stochastic values calculated with those 'risky' basic data. Various scenarios for different cases of risk behaviour are formulated and solved using decision rules. The optimal LP results are interpreted in deterministic and stochastic ways. (C) 1999 Elsevier Science B.V. All rights reserved.
This paper surveys the current state of the literature in management science/operations research approaches to air pollution management, After introducing suitable background we provide some of the institutional and l...
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This paper surveys the current state of the literature in management science/operations research approaches to air pollution management, After introducing suitable background we provide some of the institutional and legal framework needed to understand the continuing regulatory efforts in United States. Attention is then turned to mathematical programmingmodels ranging from fairly simple deterministic linear programs to quite sophisticated stochastic models which have appeared in the literature dealing with these topics, This is followed by extensions reflecting some of the work we have undertaken in association with the Texas Natural Resource Conservation Commission, a regulatory agency in Texas, Application and potential use of models is the central theme of this survey, Issues for future research are presented at the end and an extensive list of publications is provided in the references at the end of the article. Principal air quality issues of local, national, and international concern are listed below in increasing order of difficulty based on the number of different types of pollutants and problems in quantification of the risks the pollutants pose: 1. Stratospheric ozone depletion: one relatively easily controllable class of trace gases - ozone depleting chemicals, or ODCs, principally chloroflurocarbons (CFCs) - with relatively well quantified risks;2. Criteria pollutants: six common pollutants - ozone (O-3), carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2), lead (Pb), and particulate matter less than 10 microns in size (PM10) - regulated since 1970 in the U.S. and presenting relatively well quantified risks;3. Acid precipitation: two relatively easily controllable classes of trace gases - oxides of nitrogen (NOx) and oxides of sulfur (SOx) with relatively well quantified risks;4. Global warming/climate change: a few difficult to control trace gases - principally carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), and CFCs - with hi
We use the models of cognitive psychology and the early literature on linear programming models to understand how experts organize their thinking about models. We show that several different patterns appear in the way...
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We use the models of cognitive psychology and the early literature on linear programming models to understand how experts organize their thinking about models. We show that several different patterns appear in the way models are related to each other. This paper also is a kind of cognitive history of the formulation of linear programming models in the first decade after the invention of the field.
One of the major requirements of distributed multimedia applications is the need to maintain often complex, real-time synchronization constraints, More specifically, it is necessary to be able to manage arbitrary intr...
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One of the major requirements of distributed multimedia applications is the need to maintain often complex, real-time synchronization constraints, More specifically, it is necessary to be able to manage arbitrary intra- and inter-media synchronization across activities in the distributed environment. Furthermore, it is important that such developments are integrated into emerging object-oriented standards for distributed computing. This paper presents an object-oriented programming model and associated implementation to meet these requirements. The main concepts behind the proposed approach are, firstly, the use of reactive objects for real-time control and synchronization and, secondly, quality of service controlled bindings for predictable communication between objects, The flexibility of the approach is demonstrated by three contrasting examples of real-time synchronization. The implementation extends the realtime capabilities of the Chorus micro-kernel by introducing the concepts of rtports, rthandlers and quality of service controlled connections, The paper demonstrates how reactive objects and bindings are realized on this infrastructure.
In this paper we present a new formulation for the Capacitated Minimal Spanning Tree (CMST) problem. One advantage of the new formulation is that ii is more compact (in the number of constraints) than a well-known for...
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In this paper we present a new formulation for the Capacitated Minimal Spanning Tree (CMST) problem. One advantage of the new formulation is that ii is more compact (in the number of constraints) than a well-known formulation. Additionally, we show that the linearprogramming relaxation of both formulations produces optimal solutions with the same cost. We present a brief discussion concerning valid inequalities for the CMST which are directly derived from the new formulation. We show that some of the new inequalities are nor dominated by some sets of facet-inducing inequalities for the CMST. We derive some Lagrangian relaxation-based methods from the new formulation and present computational evidence showing that reasonable improvements on the original linearprogramming bounds can be obtained if these methods are strengthened by the use of cutting planes. The reported computational results indicate that one of the methods presented in this paper dominates, in most of the cases, the previous best methods reported in the literature. The most significant improvements are obtained in the instances with the root in the corner.
This paper presents a new algorithm for generating radial basis function (RBF)-like nets for classification problems. The method uses linearprogramming (LP) models to train the RBF-like net. Polynomial time complexit...
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This paper presents a new algorithm for generating radial basis function (RBF)-like nets for classification problems. The method uses linearprogramming (LP) models to train the RBF-like net. Polynomial time complexity of the method is proven and computational results are provided for many, well-known problems. The method can also be implemented as an on-line adaptive algorithm.
Scenarios are a useful tool to study the effects of changes in the socio-economic and/or biophysical environment on agricultural land use. For the analysis of these scenarios an operational methodology, denominated US...
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Scenarios are a useful tool to study the effects of changes in the socio-economic and/or biophysical environment on agricultural land use. For the analysis of these scenarios an operational methodology, denominated USTED, has been developed. The methodology is based on a linearprogramming model in combination with GIS, crop growth simulation models, and expert systems. The data requirements include quantitative descriptions of land use systems and technologies, attribute data on e.g. prices and chemical compositions, and georeferenced data on farms and soils. Sustainability is incorporated in the methodology by a limited number of quantified sustainability parameters. The linearprogramming model analyses, on the basis of different farm types, the effect of different scenarios on land use. Customized computer software (MODUS) operationalises the integration of the different models. The methodology is illustrated with a case study for the Neguev settlement in the Atlantic Zone of Costa Rica.
In India and other developing countries, irrigation has received particular attention for stimulating economic growth. Increase in agricultural productivity through better inputs is considered the key to economic deve...
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In India and other developing countries, irrigation has received particular attention for stimulating economic growth. Increase in agricultural productivity through better inputs is considered the key to economic development and self sufficiency. Considering the cost increases incurred by the state-run electricity utilities in rural electrification and the uncertainties pertaining to the supply and the price of liquid hydrocarbon fuels, it becomes imperative to identify other options for irrigation water pumping. Much work has been done in recent years in India and elsewhere on the use of alternative technologies for this purpose, and the present work attempts to develop a linear (mixed integer) model for determining the cost-effective technology options at the micro level. The energy required for irrigation is estimated. This is followed by a mathematical description of the developed model. The authors also discuss the technoeconomics of different energy resource and technology options for the irrigation sector. The technologies include solar photovoltaics, water pumping windmills, gasifier and biogas plants coupled to diesel engines operating in the dual-fuel mode, electric pumpsets, and diesel pumps in the independent mode. The developed model is solved for typical conditions that exist in India, and it is shown that there are conditions in which alternative energy technologies make economic sense.
Focuses on heuristic solution procedures for a mixed-integer programming discriminant model. Comparison between mixed-integer programmingmodels and linear programming models' accuracy; Use of the Monte Carlo simu...
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Focuses on heuristic solution procedures for a mixed-integer programming discriminant model. Comparison between mixed-integer programmingmodels and linear programming models' accuracy; Use of the Monte Carlo simulation method in comparing the heuristics with mixed-integer models.
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