An algorithm for optimizing network flow capacity under economies of scale

Bansai, P. P. ; Jacobsen, S. E.
Springer
Published 1975
ISSN:
1573-2878
Keywords:
Nonconvex programming ; network flows ; mathematical programming ; network synthesis ; operations research
Source:
Springer Online Journal Archives 1860-2000
Topics:
Mathematics
Notes:
Abstract The problem of optimally allocating a fixed budget to the various arcs of a single-source, single-sink network for the purpose of maximizing network flow capacity is considered. The initial vector of arc capacities is given, and the cost function, associated with each arc, for incrementing capacity is concave; therefore, the feasible region is nonconvex. The problem is approached by Benders' decomposition procedure, and a finite algorithm is developed for solving the nonconvex relaxed master problems. A numerical example of optimizing network flow capacity, under economies of scale, is included.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF00933746
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autor Bansai, P. P.
Jacobsen, S. E.
autorsonst Bansai, P. P.
Jacobsen, S. E.
book_url http://dx.doi.org/10.1007/BF00933746
datenlieferant nat_lic_papers
hauptsatz hsatz_simple
identnr NLM197956912
iqvoc_descriptor_keyword iqvoc_00000483:programming
iqvoc_00000154:mathematical programming
iqvoc_00000153:operations research
issn 1573-2878
journal_name Journal of optimization theory and applications
materialart 1
notes Abstract The problem of optimally allocating a fixed budget to the various arcs of a single-source, single-sink network for the purpose of maximizing network flow capacity is considered. The initial vector of arc capacities is given, and the cost function, associated with each arc, for incrementing capacity is concave; therefore, the feasible region is nonconvex. The problem is approached by Benders' decomposition procedure, and a finite algorithm is developed for solving the nonconvex relaxed master problems. A numerical example of optimizing network flow capacity, under economies of scale, is included.
package_name Springer
publikationsjahr_anzeige 1975
publikationsjahr_facette 1975
publikationsjahr_intervall 8024:1975-1979
publikationsjahr_sort 1975
publisher Springer
reference 15 (1975), S. 565-586
schlagwort Nonconvex programming
network flows
mathematical programming
network synthesis
operations research
search_space articles
shingle_author_1 Bansai, P. P.
Jacobsen, S. E.
shingle_author_2 Bansai, P. P.
Jacobsen, S. E.
shingle_author_3 Bansai, P. P.
Jacobsen, S. E.
shingle_author_4 Bansai, P. P.
Jacobsen, S. E.
shingle_catch_all_1 Bansai, P. P.
Jacobsen, S. E.
An algorithm for optimizing network flow capacity under economies of scale
Nonconvex programming
network flows
mathematical programming
network synthesis
operations research
Nonconvex programming
network flows
mathematical programming
network synthesis
operations research
Abstract The problem of optimally allocating a fixed budget to the various arcs of a single-source, single-sink network for the purpose of maximizing network flow capacity is considered. The initial vector of arc capacities is given, and the cost function, associated with each arc, for incrementing capacity is concave; therefore, the feasible region is nonconvex. The problem is approached by Benders' decomposition procedure, and a finite algorithm is developed for solving the nonconvex relaxed master problems. A numerical example of optimizing network flow capacity, under economies of scale, is included.
1573-2878
15732878
Springer
shingle_catch_all_2 Bansai, P. P.
Jacobsen, S. E.
An algorithm for optimizing network flow capacity under economies of scale
Nonconvex programming
network flows
mathematical programming
network synthesis
operations research
Nonconvex programming
network flows
mathematical programming
network synthesis
operations research
Abstract The problem of optimally allocating a fixed budget to the various arcs of a single-source, single-sink network for the purpose of maximizing network flow capacity is considered. The initial vector of arc capacities is given, and the cost function, associated with each arc, for incrementing capacity is concave; therefore, the feasible region is nonconvex. The problem is approached by Benders' decomposition procedure, and a finite algorithm is developed for solving the nonconvex relaxed master problems. A numerical example of optimizing network flow capacity, under economies of scale, is included.
1573-2878
15732878
Springer
shingle_catch_all_3 Bansai, P. P.
Jacobsen, S. E.
An algorithm for optimizing network flow capacity under economies of scale
Nonconvex programming
network flows
mathematical programming
network synthesis
operations research
Nonconvex programming
network flows
mathematical programming
network synthesis
operations research
Abstract The problem of optimally allocating a fixed budget to the various arcs of a single-source, single-sink network for the purpose of maximizing network flow capacity is considered. The initial vector of arc capacities is given, and the cost function, associated with each arc, for incrementing capacity is concave; therefore, the feasible region is nonconvex. The problem is approached by Benders' decomposition procedure, and a finite algorithm is developed for solving the nonconvex relaxed master problems. A numerical example of optimizing network flow capacity, under economies of scale, is included.
1573-2878
15732878
Springer
shingle_catch_all_4 Bansai, P. P.
Jacobsen, S. E.
An algorithm for optimizing network flow capacity under economies of scale
Nonconvex programming
network flows
mathematical programming
network synthesis
operations research
Nonconvex programming
network flows
mathematical programming
network synthesis
operations research
Abstract The problem of optimally allocating a fixed budget to the various arcs of a single-source, single-sink network for the purpose of maximizing network flow capacity is considered. The initial vector of arc capacities is given, and the cost function, associated with each arc, for incrementing capacity is concave; therefore, the feasible region is nonconvex. The problem is approached by Benders' decomposition procedure, and a finite algorithm is developed for solving the nonconvex relaxed master problems. A numerical example of optimizing network flow capacity, under economies of scale, is included.
1573-2878
15732878
Springer
shingle_title_1 An algorithm for optimizing network flow capacity under economies of scale
shingle_title_2 An algorithm for optimizing network flow capacity under economies of scale
shingle_title_3 An algorithm for optimizing network flow capacity under economies of scale
shingle_title_4 An algorithm for optimizing network flow capacity under economies of scale
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source_archive Springer Online Journal Archives 1860-2000
timestamp 2024-05-06T09:56:00.662Z
titel An algorithm for optimizing network flow capacity under economies of scale
titel_suche An algorithm for optimizing network flow capacity under economies of scale
topic SA-SP
uid nat_lic_papers_NLM197956912