Separable convexification and DCA techniques for capacity and flow assignment problems
P. Mahey; Thai Q. Phong; H. P. L. Luna
RAIRO - Operations Research - Recherche Opérationnelle (2001)
- Volume: 35, Issue: 2, page 269-281
- ISSN: 0399-0559
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topMahey, P., Phong, Thai Q., and Luna, H. P. L.. "Separable convexification and DCA techniques for capacity and flow assignment problems." RAIRO - Operations Research - Recherche Opérationnelle 35.2 (2001): 269-281. <http://eudml.org/doc/105246>.
@article{Mahey2001,
abstract = {We study a continuous version of the capacity and flow assignment problem (CFA) where the design cost is combined with an average delay measure to yield a non convex objective function coupled with multicommodity flow constraints. A separable convexification of each arc cost function is proposed to obtain approximate feasible solutions within easily computable gaps from optimality. On the other hand, DC (difference of convex functions) programming can be used to compute accurate upper bounds and reduce the gap. The technique is shown to be effective when topology is assumed fixed and capacity expansion on some arcs is considered.},
author = {Mahey, P., Phong, Thai Q., Luna, H. P. L.},
journal = {RAIRO - Operations Research - Recherche Opérationnelle},
keywords = {network design; DC optimization; capacity and flow assignment},
language = {eng},
number = {2},
pages = {269-281},
publisher = {EDP-Sciences},
title = {Separable convexification and DCA techniques for capacity and flow assignment problems},
url = {http://eudml.org/doc/105246},
volume = {35},
year = {2001},
}
TY - JOUR
AU - Mahey, P.
AU - Phong, Thai Q.
AU - Luna, H. P. L.
TI - Separable convexification and DCA techniques for capacity and flow assignment problems
JO - RAIRO - Operations Research - Recherche Opérationnelle
PY - 2001
PB - EDP-Sciences
VL - 35
IS - 2
SP - 269
EP - 281
AB - We study a continuous version of the capacity and flow assignment problem (CFA) where the design cost is combined with an average delay measure to yield a non convex objective function coupled with multicommodity flow constraints. A separable convexification of each arc cost function is proposed to obtain approximate feasible solutions within easily computable gaps from optimality. On the other hand, DC (difference of convex functions) programming can be used to compute accurate upper bounds and reduce the gap. The technique is shown to be effective when topology is assumed fixed and capacity expansion on some arcs is considered.
LA - eng
KW - network design; DC optimization; capacity and flow assignment
UR - http://eudml.org/doc/105246
ER -
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