|
Summary: ¢¡¤£¤¥§¦©¨¡¤¨ !¥"¨$#%¡¤&¥"¨')(10
2 35476 8 9§4A@ B C 3ED5F GIH PRQSQUT&V¢W
X`YbadcfehgpirqtsuiwvxywqtsY ic y ira Yvh$s ywvvh$Ybv X yadY
ciwv e Ybvhgfhgqji e Yusuir klinmh$iwq o apiirvhgq¢ mRcrirv
Xtihshqsytmbs X`Y xYuSqvY wxviiyv¤yw m
z|{f}~{h}h %I%rSbu§Rh
}tbb¤u
¢¡¤£¢£¥d¦p§©¨1ª¦¬«©¬¥¯®%¦±°²±³1´µ²¯¶²¦¬®%²·¸¹²º¬»¼©¹¶¬·½°²¾¬°¿¢ ²¦fÀ°¬·Á©¦±¥d·ÄéºÅgÆ¢¡Ç¡Ç®%¢°ÈºÉ»ÊÌˬËÎͩϱЬÑÓÒÎͬͲÒ
ÔÉ·¸¹¦¢¨Õ¬Ö¬Ë±ÑÓÒÒ¬Õ±ÑÓÒˬ׬ϤØÙ±©Ú¨Õ¬ÖˤÑÛÒ¬Ò¬Õ±ÑÍÍ©ÜÜØbÝÞ®%¬·½¡½¨·½°²³ß¢à®%²¯¶Èáâ¹ÆÈᦩ£ÎƵØhÀvãä¨Þ¶©Û¯«È¨åå²ââ$â᧸©·æáâv¹ÆÈᦲ£Æ¬å¢®²¯¶
Self-Concordance of a Volumetric Barrier Suitable for Deriving
Decomposition Algorithms for Stochastic Semidefinite Programs
K. A. Ariyawansa
and Yuntao Zhu
Abstract
Ariyawansa and Zhu [3] have recently proposed a new class of optimization problems termed
stochastic semidefinite programs (SSDP's). SSDP's may be viewed as an extension of two-stage
stochastic (linear) programs with recourse (SLP's). Zhao [16] has derived a decomposition algo-
rithm for SLP's based on a logarithmic barrier and proved its polynomial complexity. Mehrotra
and ¨Ozevin [9] have extended the work of Zhao [16] to the case of SSDP's to derive a polyno-
mial logarithmic barrier decomposition algorithm for SSDP's. An alternative to the logarithmic
|
