Cost Functions From Cross-Section Data—Fact or Fantasy?

Production and cost functions have long been recognized as vital components of economic analyses relating to the individual firm. The U.S. Department of Agriculture, beginning with the pioneering work of T V. J. Spillman, has been a continuing participant in their empiric and theoretical development. Whereas early work emphasized farm production and cost functions, much attention has centered lately on the marketing firm. This attention has brought into sharper focus certain organizational and operating characteristics of plants. With growing interest in the marketing area, the work in the Department expanded to include cooperative research with several State experiment stations. A major such effort has involved the Marketing Economics Division, Economic Research Service, and the California Agricultural Experiment Station. This is the first of three papers prepared for publication in Agricultural Economics Research to reflect some aspects of theoretical and methodological developments in these studies. The following paper comments on, and extends the results of, a statistical analysis of costs in the operation of feed mills developed in a cooperative study with the Iowa Agricultural Experiment Station, and reported in this journal by Richard Phillips in 1956. In a second paper the authors will deal with the possibilities of developing production and cost functions from more detailed analysis of accounting records of individual firms. A third paper will discuss the technique of plant cost synthesis. This report grew out of research in plant cost and efficiency carried on cooperatively by the Marketing Economics Division, Economic Research Service, and the Giannini Foundation of Agricultural E conomics,University of California at Berkeley. The authors are indebted to L. L. Sammet, B. C. French, and D. B. DeLoach of the University of California, and W. F. Finner and V. J. Brensike of the Economic Research Service, U.S. Department of Agriculture, for their helpful suggestions during the preparation of this paper

Universal Facility Location

In the Universal Facility Location problem we are given a set of demand points and a set of facilities

Finding Facilities Fast

Clustering can play a critical role in increasing the performance and lifetime of wireless networks. The facility location problem is a general abstraction of the clustering problem and this paper presents the first constant-factor approximation algorithm for the facility location problem on unit disk graphs (UDGs), a commonly used model for wireless networks. In this version of the problem, connection costs are not metric, i.e., they do not satisfy the triangle inequality, because connecting to a non-neighbor costs ∞. In non-metric settings the best approximation algorithms guarantee an O(log n)-factor approximation, but we are able to use structural properties of UDGs to obtain a constant-factor approximation. Our approach combines ideas from the primal-dual algorithm for facility location due to Jain and Vazirani (JACM, 2001) with recent results on the weighted minimum dominating set problem for UDGs (Huang et al., J. Comb. Opt., 2008). We then show that the facility location problem on UDGs is inherently local and one can solve local subproblems independently and combine the solutions in a simple way to obtain a good solution to the overall problem. This leads to a distributed version of our algorithm in the LOCAL model that runs in constant rounds and still yields a constant-factor approximation. Even if the UDG is specified without geometry, we are able to combine recent results on maximal independent sets and clique partitioning of UDGs, to obtain an O(log n)-approximation that runs in O(log ∗ n) rounds

Suinocultura no Estado de Goiás: aplicação de um modelo de localização

Esta pesquisa teve como principal objetivo a análise da distribuição mais eficiente de granjas suinícolas no Estado de Goiás. O modelo de localização desenvolvido envolveu uma estrutura de programação inteira mista. Os fatores considerados para o objetivo do estudo foram os custos de transporte de grãos (milho e soja) até a granja, o custo de transporte de suínos até o abatedouro e o custo de transporte de carcaça de suíno até o mercado consumidor. Definiu-se como mercado consumidor o próprio Estado de Goiás, o Distrito Federal e os municípios de São Paulo, Rio de Janeiro e Belo Horizonte. Além disso, determinou-se também as ofertas de milho e soja de cada microrregião do Estado de Goiás, e o consumo per capita nacional de carne suína. Considerou-se três cenários, envolvendo níveis distintos de consumo per capita, sendo um o atual e os outros dois determinados de acordo com as perspectivas do setor.<br>The main purpose of this research work was to analyse the most efficient spatial distribution of pig production units in the state of Goiás. The model developed required a mixed integer programming structure. The factors considered in the model were: the grain transportation cost (corn and soybeans) from the source to the production unit, the cost of transporting the animals from the production unit to slaughterhouses and the carcass transportation cost from the slaughterhouse to retailers. The consumption market was spatialy defined as comprising the state of Goiás, the Distrito Federal and the counties of São Paulo, Rio de Janeiro and Belo Horizonte. Moreover, it was determined the supplies of corn and soybeans for each microregion in the state of Goiás and the national per capita pork consumption. Three scenarios, showing different per capita consumption levels, were considered. One of these is the current per capita consumption level and the two other were determined according to sector perspectives