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Discrete and Fractional Programming Techniques for Location Models

Name: Discrete and Fractional Programming Techniques for Location Models
Brand: Springer
SKU: 02716369
Price: 130.04 EUR
Availability: InStock
Author: A. I. Barros
ISBN: 9780792350026

A. I. Barros

Език

Английски език

Книга С твърди корици

Код Либристо: 02716369

Издателство Springer, април 1998

At first sight discrete and fractional programming techniques appear to be two com pletely unrelated... Цялото описание

Код Либристо: 02716369

315 b

130.04 €

254.33 лв

Външен склад в ограничено количество Изпращаме след 13-18 дни

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At first sight discrete and fractional programming techniques appear to be two com pletely unrelated fields in operations research. We will show how techniques in both fields can be applied separately and in a combined form to particular models in location analysis. Location analysis deals with the problem of deciding where to locate facilities, con sidering the clients to be served, in such a way that a certain criterion is optimized. The term "facilities" immediately suggests factories, warehouses, schools, etc. , while the term "clients" refers to depots, retail units, students, etc. Three basic classes can be identified in location analysis: continuous location, network location and dis crete location. The differences between these fields arise from the structure of the set of possible locations for the facilities. Hence, locating facilities in the plane or in another continuous space corresponds to a continuous location model while finding optimal facility locations on the edges or vertices of a network corresponds to a net work location model. Finally, if the possible set of locations is a finite set of points we have a discrete location model. Each of these fields has been actively studied, arousing intense discussion on the advantages and disadvantages of each of them. The usual requirement that every point in the plane or on the network must be a candidate location point, is one of the mostly used arguments "against" continuous and network location models.