MARC record from Internet Archive

LEADER: 02238nam 2200313 a 45 0
001 a183317
008 970327s1993 cau b f000|0 eng d
040 $aCMontNP$cCMontNP
086 0 $aD 208.14/2:NPS-OR-93-008
100 1 $aBrown, Gerald Gerard.
245 10 $aDynamic factorization in large-scale optimization /$cGerald G. Brown, Michael P. Olson.
260 0 $aMonterey, Calif. :$bNaval Postgraduate School ;$aSpringfield, Va. :$bAvailable from National Technical Information Service,$c[1993].
300 $ai, 36 p. ;$c28 cm.
500 $aCover title.
500 $a"NPS-OR-93-008."
500 $a"March 15, 1990."
500 $a"(Revised March 12, 1993)."
500 $aAD A263 993.
504 $aIncludes bibliographical references (p. 33-36).
520 $aFactorization of linear programming (LP) models enables a large portion of the LP tableau to be represented implicitly and generated from the remaining explicit part. Dynamic factorization admits algebraic elements which change in dimension during the course of solution. A unifying mathematical framework for dynamic row factorization is presented with three algorithms which derive from different LP model row structures: generalized upper bound rows, pure network rows, and generalized network rows. Each of these structures is a generalization of its predecessors, and each corresponding algorithm exhibits just enough additional richness to accommodate the structure at hand within the unified framework. Implementation and computational results are presented for a variety of real-world models. These results suggest that each of these algorithms is superior to the traditional, non-factorized approach, with the degree of improvement depending upon the size and quality of the row factorization identified.
592 $aaq/aq cc:9116 03/27/97.
650 4 $aLINEAR PROGRAMMING.
650 4 $aFACTOR ANALYSIS.
650 4 $aOPTIMIZATION.
700 1 $aOlson, Michael P.
710 2 $aNaval Postgraduate School (U.S.).$bDept. of Operations Research.
740 01 $aNPS-OR-93-008.
926 $aNPS-LIB$bFEDDOCS$cD 208.14/2:NPS-OR-93-008$dBOOK$f1
926 $aNPS-LIB$bFEDDOCS$cD 208.14/2:NPS-OR-93-008$dBOOK$f2