This paper provides a method for formulating linear programming models in which one or more factors have upward sloping supply schedules, and the prices of these factors are to be endogenously determined at either the...
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This paper provides a method for formulating linear programming models in which one or more factors have upward sloping supply schedules, and the prices of these factors are to be endogenously determined at either their competitive market equilibrium values or at the levels set by a monopsonist. The method for achieving these results utilizes the sum. over the relevant factor markets, of the producers' and consumers' surplus, and is an extension of existing methods for solving price endogenous models of product markets. [ABSTRACT FROM AUTHOR]
Argues against the importance of obtaining unbiased results from aggregate models as stated in a study on aggregation in linearprogramming. Summary of results; Clarifications; Basis for the author's belief on th...
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Argues against the importance of obtaining unbiased results from aggregate models as stated in a study on aggregation in linearprogramming. Summary of results; Clarifications; Basis for the author's belief on the result's importance. [ABSTRACT FROM AUTHOR]
Three sets of sufficient conditions for exact aggregation of linear programming models are discussed. They provide a relaxation of the proportionality and dimensionality conditions among elements of the micro problems...
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Three sets of sufficient conditions for exact aggregation of linear programming models are discussed. They provide a relaxation of the proportionality and dimensionality conditions among elements of the micro problems required by R.H. Day's specification. For correct aggregation it is not necessary to classify firms according to 'homogeneity' criteria. [ABSTRACT FROM AUTHOR]
Deals with multiple primal and dual optimal solutions in linearprogramming (LP) problems. Criterion to help the researcher choose among various optimal solutions; Validation of LP models; Role of multiple optimal sol...
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Deals with multiple primal and dual optimal solutions in linearprogramming (LP) problems. Criterion to help the researcher choose among various optimal solutions; Validation of LP models; Role of multiple optimal solutions in the validation of economic models analyzed by LP.
Interval multiplicative preference relation is very useful in expressing decision maker's preferences on alternatives under uncertain preference information. How to derive priorities from a interval multiplicative...
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ISBN:
(纸本)9781424423873
Interval multiplicative preference relation is very useful in expressing decision maker's preferences on alternatives under uncertain preference information. How to derive priorities from a interval multiplicative preference relation is an interesting and important issue in decision making. In this paper,we first define the concepts of interval multiplicative preference relations, consistent interval multiplicative preference relations, and then propose some simple and practical linear programming models, based on consistent interval multiplicative preference relations for obtaining the priority vector of interval multiplicative preference relations. These linear programming models are also extended to obtain the collective priority vector of several interval multiplicative preference relations. Finally, the proposed models are tested and examined with two numerical examples and prove to be simple, effective and practical.
Comments on an article which used multiple optimal solutions in linear programming models. Presence of multiple optima and degeneracy in related literature; Effects of alternative optima in a linearprogramming analys...
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Comments on an article which used multiple optimal solutions in linear programming models. Presence of multiple optima and degeneracy in related literature; Effects of alternative optima in a linearprogramming analysis of urban development plans.
Deriving priority weights from fuzzy preference relations is a significant issue in decision making problems. In this paper, based on the definition of additive consistent fuzzy preference relations proposed by Tanino...
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Deriving priority weights from fuzzy preference relations is a significant issue in decision making problems. In this paper, based on the definition of additive consistent fuzzy preference relations proposed by Tanino, a new approach with a parameter is developed to obtain priority weights, and properties of the new approach are explored. Then, a method for correcting inconsistent fuzzy preference relations is derived, and a new definition for the additive consistent interval fuzzy preference relations is obtained for the interval complementary pairwise comparison matrix. From these, linear programming models for generating interval priority weights from additive consistent or inconsistent interval fuzzy preference relations are established. Finally, three numerical examples are examined to show the feasibility of the developed method, and comparisons are also made between this new approach and the methods proposed by Xu and Chen [15]. Through the numerical examples, the ranking of interval priority weights using the different methods was found to be the same but with a slightly different degree of possibility. However, for the same interval complementary pairwise comparison matrix, the new definition for additive consistent interval fuzzy preference relations proposed in this paper was found to have more consistent information. (C) 2011 Elsevier 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
For a stochastic programming problem with simple recourse, we show how to formulate and analyze a model that encodes the common risk attitude of decreasing risk aversion. We discuss a class of linear fractional utilit...
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For a stochastic programming problem with simple recourse, we show how to formulate and analyze a model that encodes the common risk attitude of decreasing risk aversion. We discuss a class of linear fractional utility functions that represent this risk attitude and show that for such a utility function the resulting nonlinear model can be reduced to a linearprogramming model. The linear model, moreover, has only a slight percentage increase in the number of constraints as compared with the usual linear model representing risk neutrality.
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