Discrete and Fractional Programming Techniques for Location Models:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Boston, MA
Springer US
1998
|
| Schriftenreihe: | Combinatorial Optimization
3 |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Beschreibung: | 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 |
| Beschreibung: | 1 Online-Ressource (XVIII, 180 p) |
| ISBN: | 9781461540724 9781461368243 |
| ISSN: | 1388-3011 |
| DOI: | 10.1007/978-1-4615-4072-4 |
Internformat
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| 245 | 1 | 0 | |a Discrete and Fractional Programming Techniques for Location Models |c by Ana Isabel Barros |
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| 500 | |a 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 | ||
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| discipline | Mathematik |
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| spelling | Barros, Ana Isabel Verfasser aut Discrete and Fractional Programming Techniques for Location Models by Ana Isabel Barros Boston, MA Springer US 1998 1 Online-Ressource (XVIII, 180 p) txt rdacontent c rdamedia cr rdacarrier Combinatorial Optimization 3 1388-3011 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 Mathematics Computational complexity Algorithms Combinatorics Mathematical optimization Calculus of Variations and Optimal Control; Optimization Optimization Discrete Mathematics in Computer Science Mathematik Optimierung (DE-588)4043664-0 gnd rswk-swf 1\p (DE-588)4113937-9 Hochschulschrift gnd-content Optimierung (DE-588)4043664-0 s 2\p DE-604 https://doi.org/10.1007/978-1-4615-4072-4 Verlag Volltext 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk 2\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Barros, Ana Isabel Discrete and Fractional Programming Techniques for Location Models Mathematics Computational complexity Algorithms Combinatorics Mathematical optimization Calculus of Variations and Optimal Control; Optimization Optimization Discrete Mathematics in Computer Science Mathematik Optimierung (DE-588)4043664-0 gnd |
| subject_GND | (DE-588)4043664-0 (DE-588)4113937-9 |
| title | Discrete and Fractional Programming Techniques for Location Models |
| title_auth | Discrete and Fractional Programming Techniques for Location Models |
| title_exact_search | Discrete and Fractional Programming Techniques for Location Models |
| title_full | Discrete and Fractional Programming Techniques for Location Models by Ana Isabel Barros |
| title_fullStr | Discrete and Fractional Programming Techniques for Location Models by Ana Isabel Barros |
| title_full_unstemmed | Discrete and Fractional Programming Techniques for Location Models by Ana Isabel Barros |
| title_short | Discrete and Fractional Programming Techniques for Location Models |
| title_sort | discrete and fractional programming techniques for location models |
| topic | Mathematics Computational complexity Algorithms Combinatorics Mathematical optimization Calculus of Variations and Optimal Control; Optimization Optimization Discrete Mathematics in Computer Science Mathematik Optimierung (DE-588)4043664-0 gnd |
| topic_facet | Mathematics Computational complexity Algorithms Combinatorics Mathematical optimization Calculus of Variations and Optimal Control; Optimization Optimization Discrete Mathematics in Computer Science Mathematik Optimierung Hochschulschrift |
| url | https://doi.org/10.1007/978-1-4615-4072-4 |
| work_keys_str_mv | AT barrosanaisabel discreteandfractionalprogrammingtechniquesforlocationmodels |