Maximum Likelihood from Incomplete Data via the EM Algorithm
6 Apr 2007 GOOD I. J. (1965) The Estimation of Probabilities: An Essay on Modern Bayesian Methods. Cambridge
Dimitri P. Bertsekas a and David A. Castanon b 1. Introduction
Assignment problem auction algorithm; synchronous and asynchronous Linear Network Optimization: Algorithms and Codes (MIT Press
A Distributed Algorithm for the Assignment Problem
This paper describes a new algorithm for solving the classical assignment in developing distributed algorithms for optimization and other problems.
Mathematical Equivalence of the Auction Algorithm for Assignment
2 Laboratory for Information and Decision Systems M.I.T
A FORWARD/REVERSE AUCTION ALGORITHM FOR
2 Department of Electrical Engineering and Computer Science M. I. T.
An Auction Algorithm for Shortest Paths
AN AUCTION ALGORITHM FOR SHORTEST PATHS*. DIMITRI P. BERTSEKAS'. Abstract. A new and simple algorithm for finding shortest paths in a directed graph is
Gaussian mixture models and the EM algorithm
Expectation-Maximization (EM) algorithm first for the specific case of GMMs
Auction Algorithms
Auction Algorithms. Dimitri P. Bertsekas bertsekas@lids.mit.edu. Laboratory for Information and Decision Systems. Massachusetts Institute of Technology.
D.P. Bertsekas 1. INTRODUf;rION Relaxation methods for optimal
The algorithm can also be inter- preted as a Jacobi -like relaxation method for solving a dual problem. Its. (sequential) worst -case complexity for a
Rollout Algorithms for Discrete Optimization: A Survey
dimitrib@mit.edu This chapter discusses rollout algorithms a sequential approach to ... A rollout algorithm starts from some given heuristic.
ANAUCTIONALGORITHMFORSHORTESTPATHS*
DIMITRIP.BERTSEKAS'
algorithmterminates. processusingsimpledatastructures.425Downloaded 10/30/14 to 128.31.7.81. Redistribution subject to SIAM license or copyright; see http://www.siam.org/journals/ojsa.php
426DIMITRIP.BERTSEKAS
algorithm'sperformance. whichisverysimilartotheoneprovidedhere. thepresentpaper.7containscomputationalresults.
formforthesingleoriginandsingledestinationcase,andwedeferthediscussionofDownloaded 10/30/14 to 128.31.7.81. Redistribution subject to SIAM license or copyright; see http://www.siam.org/journals/ojsa.php
AUCTIONFORSHORTESTPATHS427
ofnodes. ofitsarclengths. (1,i,i_,ik-). that (la)p,<-aij+pV(i,j), weimplicitlyassumethatPissimple.) thedefaultpairP(1),p,=O
apair.Downloaded 10/30/14 to 128.31.7.81. Redistribution subject to SIAM license or copyright; see http://www.siam.org/journals/ojsa.php
428DIMITRIP.BERTSEKAS
TYPICALITERATION
LetbetheterminalnodeofP.If
(2)pPi:=min{ao+pj},i,j)4
(4) andif1,contractP.Gotothenextiteration.Step2:(Extendpath).ExtendPbynodejiwhere
jiargmin{ai+p}.(i,j)e nextiteration. typicalwhentheinitialpricesareallzero. theshortestdistancefromtoj. min{aj+p},(5)p,, cf.condition(4)).Supposenextthat
pAUCTIONFORSHORTESTPATHS429
P2=2 2plOration
P3=2Iteration
PathPPricevectorpTypeofaction
kP.Thiscompletestheinductionproof. lastassertionoftheproposition. fromtheorigintotheterminalnodeofP. algorithm, pl-pj<=DjVjcdf, whilebyProposition2,wehavePl--PDiforallinP.Downloaded 10/30/14 to 128.31.7.81. Redistribution subject to SIAM license or copyright; see http://www.siam.org/journals/ojsa.php
430DIMITRIP.BERTSEKAS
Itfollowsthat
Di+pipt<-_Dj+pjptlPandj.
mayviewthequantityDj+p-pt
algorithm'spathonlyifD+p-p,isminimal. pationinashortestpathfrom1tot. nodes. (7)pOinitialpriceofnodei. (8)d,D,+pLetusindextheiterationsby1,2,..,andlet
(b)IfkAUCTIONFORSHORTESTPATHS431
toi,implyingthatp-->oo.U (10)#-{ild,<=d,}; pathsgeneratedbythealgorithm.Letusdenote (11)!numberofnodesin#, andletusalsodenotebyEtheproduct (13)E=I.G. runningtimeofthealgorithmisO(E(D,+p-p)).1),itfollowsthat
(14)pi-Pi432DIMITRIP.BERTSEKAS
NotethatwehaveDt<-_hL,where
(15)Lmaxaij,(i,j) (17)O(EhL).OriginDestination
roughlyequaltotwo)by n,-l+(2n,1),,q,i problemofFig.1,theaboveestimateisexact. andthedirectionofeacharc.assumethatallarclengthsarenonnegative.WeintroduceaversionofthealgorithmDownloaded 10/30/14 to 128.31.7.81. Redistribution subject to SIAM license or copyright; see http://www.siam.org/journals/ojsa.php
AUCTIONFORSHORTESTPATHS433
lengthsandstartingprices.Let (18)K=[logLJ+l andfork=1,...,K,define (19)ao(k)=2K_kV(i,j)e binaryrepresentationofa0.Define nextsection. (21)p(k+l)=2p*(k)VieW, p,.():ovi. (22)O<-ao(k+l)-2ao(k)<-IV(i,j)s,CScondition
(23)p(k+l)<=py(k+l)+ao(k+l)V(i,j)s allthesubproblems.Itcanbeseenusing(22)that
D,(k+1)=<2D,(k)+h(k),
andinviewof(21),weobtain k,k=k+l,.,K,is(25)O(E(k)h(k)),Downloaded 10/30/14 to 128.31.7.81. Redistribution subject to SIAM license or copyright; see http://www.siam.org/journals/ojsa.php
434DIMITRIP.BERTSEKAS
timeofthealgorithmforsubproblemkis (26)O(E(k)D,(k)), aij()<2 wehave (27)D,(/7)<2h(/7). thealgorithmis (28)02E(/)h(/)+E(k)h(k)k=/+! itfollowsthatPiaiji+Pj,,
min{a+pa},aiji+PJii,j)e.g beingtheterminalnode,wecalculate min{a+p},i,j)a togetherwithanarc(i,j)suchthatjiargmin{a+p}.i,j)eagDownloaded 10/30/14 to 128.31.7.81. Redistribution subject to SIAM license or copyright; see http://www.siam.org/journals/ojsa.php
AUCTIONFORSHORTESTPATHS435
terminalnodeofthepath. computethe"bestneighbor" jiargmin{ai+p}i,j.l kargmin{a+pj},(i,j)4,jJi andthecorresponding"secondbestlevel"Wiaitqh-Pkg.
theminimumintheexpression min(aj+p},i,j.4 neighbor," kargmin{a;+p;}(i,j)P<--ai+ffiVi,j4,
thateachnodeexceptfortheoriginhasatleastoneincomingarc.Downloaded 10/30/14 to 128.31.7.81. Redistribution subject to SIAM license or copyright; see http://www.siam.org/journals/ojsa.php
436DIMITRIP.BERTSEKAS
g(t),pi=OVi, ifallarclengthsarenonnegative.TYPICALITERATIONOFTHEREVERSEALGORITHM
LetjbethestartingnodeofR.If
pj>max{Piaij},(i,j). gotoStep1;elsegotoStep2.Step1:(Contractpath).Set
pg:=max{paig},i,j) iteration.R,precedingj),where
/argmax{Pi-aij}.i,j),4 iteration.COMBINEDALGORITHM
anincreaseoftheoriginpricePl.GotoStep2. ofthedestinationpricept.GotoStep1.Step2mustcontainonlyafinitenumberofiterationsoftheforwardandthereverseDownloaded 10/30/14 to 128.31.7.81. Redistribution subject to SIAM license or copyright; see http://www.siam.org/journals/ojsa.php
AUCTIONFORSHORTESTPATHS437
counterexample. p.Initially, ={(i,j)6g[a0TYPICALPREPROCESSINGITERATION
fromgandgotoStep2.Step2:(Addaffectedarcsto).Ifp>ag+pg,set
Pi:=aij+p
Wehavethefollowingproposition.
withapricevectorpsatisfying (29)p<=ao+pgVi,j6gwithiCt. wehave{(i,j)6lpi>aq+pj,iSt}.Downloaded 10/30/14 to 128.31.7.81. Redistribution subject to SIAM license or copyright; see http://www.siam.org/journals/ojsa.php
438DIMITRIP.BERTSEKAS
distancefromktoifkt,Pk*=/,ifk=t, andletrbeasufficientlylargescalarsothat p,>-p*r (30)Pk>=Prlkt. have ai+p>ao+pj.*r>min{a,+p}rp*r,i,m),. theproof. ={(i,j)ClaoPj:--Piai
thereforefollowsfromProposition6. ofiterationswithapricevectorpsatisfyingP,<=aij+piV(i,j)ewithjl.Downloaded 10/30/14 to 128.31.7.81. Redistribution subject to SIAM license or copyright; see http://www.siam.org/journals/ojsa.php
AUCTIONFORSHORTESTPATHS439
[aij];(k)=/2K_k[V(i,j),,1-- and (31)p(k+l)<=p)?(k+l)+ij(k+l)+ll(i,j), discussesparalleltwo-sidedalgorithms. handlethepathofanotherorigin. experimentallyonasharedmemorymachine.Downloaded 10/30/14 to 128.31.7.81. Redistribution subject to SIAM license or copyright; see http://www.siam.org/journals/ojsa.php
440DIMITRIP.BERTSEKAS
Pi:=min{au+pj};i,,sd
implementation. (32)Pin:=max{p,,p}Vn. pricevectorpsatisfiesthecondition Pm= p<=a,,+p',,,p<--_a,,+pV(m,n).(33) Then, (34) and (35) and max{p'm,p}<--_a,,,.+max{p',,,p}V(m,n)M, min{pi,.,,,p}Proof.From(33),wehave
pPJmamn"k-max{pi,,,p}V(m,n)4. time-consumingifnovectorprocessinghardwareisavailableattheprocessors.Downloaded 10/30/14 to 128.31.7.81. Redistribution subject to SIAM license or copyright; see http://www.siam.org/journals/ojsa.php
AUCTIONFORSHORTESTPATHS441
condition min{cj+p}(36)Ciji-[-"pj(i,J) jargmin{ci+p};i,j), andthen" PJi+Wil.)i
price), vimin{%+pj},i,j.s wi=min{ci+p}.i,j.sC,j#ji anobject. difference;whiletheauctionalgorithmisguaranteedtoterminateinafinitenumberDownloaded 10/30/14 to 128.31.7.81. Redistribution subject to SIAM license or copyright; see http://www.siam.org/journals/ojsa.php
442DIMITRIP.BERTSEKAS
teesoptimalityofthefinalassignment. t=4 assignmentcostsareshownnexttothearcs. psatisfyingtheCScondition(la),i.e., (37)pi<=aij+pl(i,j)g, andthepartialassignment (i',i)ti#l,t. assignedarcs(i',i)iszero. min{alj+p},(1,j)d changingthepricep,.Downloaded 10/30/14 to 128.31.7.81. Redistribution subject to SIAM license or copyright; see http://www.siam.org/journals/ojsa.php
AUCTIONFORSHORTESTPATHS443
thefollowingcanbeverifiedbyinduction: (38)(1',il),(i,i2),''',(i-1,ik), togetherwiththeadditionalarcs i',i)foril,ik,t, min{c./+p}p(/,j) Piaiji"]"
theshortestpathalgorithm. (LNF)minimize,aoxo(i,j) (40)0<--xoV(i,j),91,Downloaded 10/30/14 to 128.31.7.81. Redistribution subject to SIAM license or copyright; see http://www.siam.org/journals/ojsa.php
444DIMITRIP.BERTSEKAS
where S1,S=-1,
si=Ofi#l,t, andisthegivendestination. primalcostisequaltotheoptimaldualcost. Xij__flifandjaresuccessivenodesinP,
[0otherwise. complementaryslacknessconditions p0pao+p.li,j.
changeindualcost. experimentallyonasharedmemorymachine.Downloaded 10/30/14 to 128.31.7.81. Redistribution subject to SIAM license or copyright; see http://www.siam.org/journals/ojsa.php
440DIMITRIP.BERTSEKAS
Pi:=min{au+pj};i,,sd
implementation. (32)Pin:=max{p,,p}Vn. pricevectorpsatisfiestheconditionPm= p<=a,,+p',,,p<--_a,,+pV(m,n).(33) Then, (34) and (35) and max{p'm,p}<--_a,,,.+max{p',,,p}V(m,n)M, min{pi,.,,,p}Proof.From(33),wehave
ptime-consumingifnovectorprocessinghardwareisavailableattheprocessors.Downloaded 10/30/14 to 128.31.7.81. Redistribution subject to SIAM license or copyright; see http://www.siam.org/journals/ojsa.php
AUCTIONFORSHORTESTPATHS441
condition min{cj+p}(36)Ciji-[-"pj(i,J) jargmin{ci+p};i,j), andthen"PJi+Wil.)i
price), vimin{%+pj},i,j.s wi=min{ci+p}.i,j.sC,j#ji anobject.difference;whiletheauctionalgorithmisguaranteedtoterminateinafinitenumberDownloaded 10/30/14 to 128.31.7.81. Redistribution subject to SIAM license or copyright; see http://www.siam.org/journals/ojsa.php
442DIMITRIP.BERTSEKAS
teesoptimalityofthefinalassignment. t=4 assignmentcostsareshownnexttothearcs. psatisfyingtheCScondition(la),i.e., (37)pi<=aij+pl(i,j)g, andthepartialassignment (i',i)ti#l,t. assignedarcs(i',i)iszero. min{alj+p},(1,j)dchangingthepricep,.Downloaded 10/30/14 to 128.31.7.81. Redistribution subject to SIAM license or copyright; see http://www.siam.org/journals/ojsa.php
AUCTIONFORSHORTESTPATHS443
thefollowingcanbeverifiedbyinduction: (38)(1',il),(i,i2),''',(i-1,ik), togetherwiththeadditionalarcs i',i)foril,ik,t, min{c./+p}p(/,j)Piaiji"]"
theshortestpathalgorithm. (LNF)minimize,aoxo(i,j)(40)0<--xoV(i,j),91,Downloaded 10/30/14 to 128.31.7.81. Redistribution subject to SIAM license or copyright; see http://www.siam.org/journals/ojsa.php
444DIMITRIP.BERTSEKAS
whereS1,S=-1,
si=Ofi#l,t, andisthegivendestination. primalcostisequaltotheoptimaldualcost.Xij__flifandjaresuccessivenodesinP,
[0otherwise. complementaryslacknessconditions pwheneachofthereversepathshavemettheforwardpath.Downloaded 10/30/14 to 128.31.7.81. Redistribution subject to SIAM license or copyright; see http://www.siam.org/journals/ojsa.php
AUCTIONFORSHORTESTPATHS445
thanTWO_TREE_SHEAP,asshowninTable1. possible).themeritsofouralgorithm.WealsonotethattheideasinthispaperarenewandDownloaded 10/30/14 to 128.31.7.81. Redistribution subject to SIAM license or copyright; see http://www.siam.org/journals/ojsa.php
446DIMITRIP.BERTSEKAS
1,1000].
NAAUCTION_SPSHEAPTWO_TREE_SHEAP
1,0004,0000.0330.2500.033
1,00010,0000.0500.2000.133
2,0008,0000.0170.0170.017
2,00020,0000.0670.8670.150
3,00012,0000.0670.9830.100
3,00030,0000.0331.1170.100
4,00016,0000.0671.2330.100
4,00040,0000.0330.3830.100
5,00020,0000.0501.3830.083
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