Precedence graphs generation using assembly sequences

Size: px
Start display at page:

Download "Precedence graphs generation using assembly sequences"

Transcription

1 Preedene grahs generaton usng assebly sequenes VIOREL MÎNZU* and ANTONETA BRATCU ** * Deartent of Autoat Control and Eletrons Dunãrea de Jos Unversty of Galat Str. Doneasã, Galat ROMANIA ** Laboratore d Autoatque de Besançon ENSMM - UFC - UMR 6596 Unversté de Franhe-Coté 5, Rue Alan Savary Besançon FRANCE Abstrat: - Alost all ethods dealng wth assebly systes desgn - for exale, assebly lne balanng (ALB), tasks-to-workstatons assgnent algorths, resoure lannng - are based on the artton of reedene grahs. These are dreted grahs whose nodes reresent the assebly tasks and arrows reresent the reedene relaton between tasks. In the lterature there are very effent and well-known ethods to generate assebly sequenes and a reedene grah an be obtaned by "ergng" assebly sequenes. Nevertheless, no systeat obtanng ethod for these grahs was roosed. Ths aer deals wth a roerty of a gven set of assebly sequenes, that guarantees the exstene of an "equvalent" reedene grah, after sutably defnng suh an equvalene. Ths result an be used for the general ase, when ths roerty s not et, to fnd an equvalent set of reedene grahs. Key-Words: - assebly systes, assebly sequenes, reedene grahs Introduton Preedene grahs are the ost used tools n assebly systes desgn. Assebly lne balanng ethods (see []), that gve a frst rough layout of an assebly lne, have as nut data the reedene grah. Other desgn ethods use also reedene grahs. For exale, the aroah roosed at Draer Laboratory ([8], [9]) s based on assebly task flow grah whh are essentally reedene grah wth a lnear struture. Preedene grahs n dfferent fors are also used n tasks-toworkstatons assgnent ethods ([6]) or resoure lannng ([7]). In soe aers t s roosed that reedene grahs be obtaned by "ergng" assebly sequenes ([8], [5], []). In [5], the authors roose a ethod for the generaton of the reedene grahs fro a gven set of assebly sequenes, whh s essentally based on heurst searh. The reedene grahs have two weak onts. The frst one s the fat the assebly tasks are generally not well defned. An assebly task s well defned when the base art and the seondary art are sefed. The seond weak ont s the nonexstene of a systeat obtanng ethod. On the other hand, there are very effent ethods to generate assebly sequenes (see [], [4]), whose assebly tasks are well defned. Ths aer resents a theoretal analyss, n order to answer to the queston whether there exsts a reedene grah equvalent to a gven set of assebly sequenes. Proble stateent In ths seton, we shall defne our roble, that s to fnd a reedene grah equvalent (n a sense that wll be stated below) to a gven set of assebly sequenes for a ertan rodut. Notaton: S = set of sybols, N = ard (S). We onsder that a sybol reresents a art that wll be assebled wth other arts to ake the rodut. S s the set of sybols orresondng to all arts and N s the nuber of arts. An assebly sequene s a total order over the set of arts. Hene, an assebly sequene ay be reresented by a sequene of sybols: = aa...an,, a S, () and a a f. Fro now on, we shall all olete sequene a sequene havng the for () and artal sequene a sequene of dfferent sybols whose nuber of sybols s less than N. So, an assebly sequene s reresented by a olete sequene. Let Ω be a set of olete sequenes reresentng a gven set of assebly sequenes and n = ard( Ω ): Ω = {, =,...,n}. Any olete sequene Ω, N = a a... a, ndues an order relaton over S, noted O, O S S :

2 x, y S, (x, y) O x = a, y = a k, < k We say that x reedes y and we shall note ths relaton by x < y. Obvously, O s a total order relaton over S. One an defne : I n O o = O = whh s, obvously, a artal order over S. Note that ths order s deterned by the ntal set of sequenes. Ω. The dgrah of ths relaton s G = (S, O0) and we all t reedene grah. For a gven set of sybols S and for a gven set of olete sequene Ω, the artal order relaton O0 and ts reedene grah G are unquely defned. We onsder another relaton over S: I = S S - {(a, b) S S ((a, b) O0) ((b, a) O0 )} We all I ndfferene relaton and we note (x, y) I by x?y. Defnton : A olete sequene = a eets a...a N the reedene grah G = (S, O0) f for any two values < N ether t exsts a ath n G fro a to a or a? a. Fro now on, we note by Θ the set of olete sequenes eetng the reedene grah G=(S, O0). One an say that the grah G s equvalent to the set Θ, beause G an be obtaned fro Θ and ve versa. To slfy the reresentaton of G, any arrow (a, a) s erased, f there s a ath n G fro a to a fored by at least two arrows. Exale : Let us onsder S={a, b,, d, e, f} and Ω={abdef, abdef, abdef}. The grah G orresondng to the sets S and Ω s resented here-after: a b f d e Fg. Preedene grah G=(S, O0) One an verfy that the set of sequenes eetng the reedene grah s Θ ={abdef, abdef, abdef}=ω. Hene, the reedene grah G s equvalent to the set Ω. Exale : Let s onsder S={a, b,, d, e, f, g, h} and Ω={abdefgh, abfdegh}. The grah G orresondng to the set S and Ω s resented here-after: b d e a g h f Fg. Preedene grah G= (S, O0) One an verfy that the set of sequenes eetng the reedene grah G s: Θ = abdefgh, abdefgh abdfegh, abdfegh. abfdegh, abfdegh It s easy to verfy that ths te the grah G s not equvalent to the set Ω Θ. Obvously, fro the way we have onstruted G, t holds: Ω Θ () The favorable stuaton s when Θ =Ω, beause one an onlude that the grah G= (S, O0) s equvalent to the set Ω. One an regard the onstruton Ω G Θ lke a a that defnes the set Θ for a gven Ω. One an ask the queston: does the set Ω have a roerty that guarantees the equalty Θ =Ω? In the next setons we shall show that suh a roerty exsts. The general for of a olete sequene belongng to Θ We shall note by GI = (S, I) the undreted grah of the ndfferene relaton, sly alled below as ndfferene grah. a b f d e Fg. Indfferene grah for exale. Generally, GI s not a onneted grah. Let C, =,,, be the onneted oonents of GI that ontan ore than one sybol. For the exale above, t exsts only one suh onneted oonent: C={, d, e}, whle for exale there are C={b, } and C ={d, e, f}. The varablty of olete sequenes s gven only by the sybols belongng to the onneted oonents. The other sybols have fxed ostons nsde of a olete sequene (for nstane, the sybols a, b and f n exale ). We shall all segent a gener artal sequene ade u of all sybols belongng to a onneted oonent C, =,,,. We shall note by S the segent orresondng to C. In a gven olete sequene the segent S, =,, s nstaned by the artal sequene S, =,,. In exale, there are two segents, S and S, orresondng to the two onneted oonents. A olete sequene has the for assgh, where S s ether b or b and S s ether def, dfe or fde. Theore (the for of a olete sequene eetng a reedene grah G): Θ = a b...s ( ).d e...f.s ( ).g h... ( ). k... n. Hene, Θ wll aear as the set of all nstanes of the exresson: a b...s.d e...f.s.g h.... k... n.

3 Lea : Let Θ. (ù = σ.a. σ.b. σ, a?b, σ φ) x ó :(x?a) (x?b). The roof s obvous, beause a, b and all the sybols of σ belong to the sae onneted oonent of GI. 4 The ase Ω=Θ. Neessary and suffent ondton Let onsder X a set of olete sequenes fored wth sybols of S. Fro X t an be dedued ts assoated reedene grah G X, usng the sae onstruton as above. Let s(x)={(a, b) a, b S, a? b} be the set of ars of ndfferent sybols, dedued fro G X. Note that s(ω)=s(θ). Defnton (roerty Π): Let X be a set of olete sequenes fored wth the sybols of S and E S S. If ( X, (a, b) E S S, = α.ab. β) ' = α.ba. β X we say that X has the roerty Π n relaton to the set E. In the ase E=s(X), t s sly sad that X has the roerty Π. Reark: Θ has the roerty Π. Notaton: ()=a - the sybol a has the oston n the olete sequene (a, b) - the erutaton of the sybols a and b "." - the uxtaoston oerator Lea : If there exst two olete sequenes, Θ, suh that ()=a, ()=a and <, then t exsts a olete sequene eetng G so that (+)=a and, oreover, an be obtaned fro by alyng a sequene of erutatons. Beause ()=a, one an wrte: =σ.a.σ, where σ s a artal sequene ontanng - sybols. We shall show that b σ, a?b. Suosng that x σ: a<x, t results that ( Θ, (k)=a) k. But Θ wth ()=a and >. Therefore, the suoston s false. So, we an note by b the frst sybol of σ whh s ndfferent wth a. Hene, we an wrte: =σ.axx...xb.σ and x, =... : a < x. () But a? b, so, alyng lea, we obtan: (x? a) or (x? b), x, =... (4) Fro () and (4), t follows that: x? b, x, =... Usng the roerty Π of Θ, one an aly the sequene of erutatons: (x,b) (x,b) σ.ax x (x,b)...bx x. σ σ.abx x...x. σ ' Θ (a,b) σ.bax x...x. σ ' = ' Θ... Θ; (a,b) (x,b) σ.ax x...bx. σ ' Θ We note: :(x, b), (x, b),..., (x, b), (a,b). (x,b) It s known that σ ontans - sybols, so (+)=a; besdes,, q.e.d. Consequene: If there are olete sequenes, belongng to Θ, so that ()=a, ()=a and <, then, for eah nuber k, <k<, t exsts another olete sequene belongng to Θ so that (k)=a and, oreover, an be obtaned fro by alyng a sequene of erutatons. Usng the result of theore, we ntrodue the followng Notaton: Θ : = () ()... () ( + )... ( + l) ( + l + ) l... (... ( >, =... ) ( + )... ( + l ) S ) ( + )... ( + l )... (N), S S Theore : Let, Θ be two olete sequenes: = () = ()... S (N); (N) For any,, t exsts a sequene of erutatons suh that: ' = ()... S... (N). We shall fx. To slfy the notaton, we shall wrte: =... aa...a l... ; =...bb... bl S S Obvously: { a } = { b }. If l l l k k=,,... lk k =,,... (5) a b, then frstly we shall try to obtan fro a sequene havng the sybol Beause b l ( q) = b, l (r) = a, l (r) = b l on the oston l of S. and q<r, one an aly the onsequene of lea ; hene, t exsts a sequene of erutatons,, suh that = K K l b l In the sae way, fro we shall obtan a sequene havng the sybol bl on the oston l- of S. Therefore K

4 : b = K dd K 444 K d l b l l 4444 Reark: To eet exatly the ondtons of lea, we ust have the guarantee that does not hange the oston of b l n. Ths eans we ust rove that b s not the frst sybol ndfferent wth bl. In the l S ooste stuaton, we should have < =...b l σ' b l...and x σ': b l 44 4 S So, n every sequene of Θ, all the sybols of σ should sueed bl. But s not suh a sequene. Hene, our suoston s false. We roeed n the sae way for eah sybol of S. Fnally we obtan l... x =...bb...b l and, so, the sequene of erutatons :,,..., l realses the transfer S, q.e.d. Theore : Let, Θ be two olete sequenes. Then t exsts a sequene of erutatons suh that. We wrte the sequenes and n the for (5) and we use tes the result of theore as follows: () () () : = ()... S... (N); () () () () : = ()... (N); () () ( ) () : = ()... (N); Therefore, the sequene of erutatons = (). (). (). aheves the transfer: () = ()... (N) = = ()... (N) =. In the rustanes of the onstruton Ω G Θ, resented before, we gve the an result. Theore 4 (neessary and suffent ondton for the ase Ω=Θ): Ω=Θ Ω has the roerty Π. Neessty: We know that Ω=Θ. Beause Θ has the roerty Π and s ( Θ) = s ( Ω), t follows that Ω has the roerty Π. Suffeny: We know that Ω has the roerty Π and we shall rove that Θ = Ω. Suosng that Ω Θ and onsderng the relaton (), t holds Ω Θ. Hene suh that Θ and Ω. We shall fx suh a olete sequene. Let onsder 0 Ω. Aordng to theore, there s a sequene of erutaton o, suh that : (a,b ) (ak,bk ) = (a, b ).(a, b )...(a, b ), where (a, b ) s ( Ω) = s... k k ( Θ), =...k. (a,b ) (ak,bk ) k (a,b)... Fgure 4 llustrates ths stuaton. The last erutaton nvolves by reflexvty the followng one: (b k,a k ) 0 k. Suosng that κ Ω, t follows that Ω has not the roerty Π, fat that ontradts our suoston. Hene, κ Ω. κ 0 κ Fg. 4. Sequene of erutatons By alyng the sae reasonng, t results that Ω, whh s a ontradton to our suoston. Therefore, Ω=Θ, q.e.d. 5 Use of the roerty Π One an ake an algorth that dedes whether a gven set Ω of olete sequenes has the roerty Π or not. If the answer s ostve, the reedene grah equvalent to the set of sequenes s G. If Ω has not the roerty Π, the algorth should generate the artton of Ω nto subsets havng the roerty Π, eah of the beng reresented by a reedene grah. The arttonng anner ay be subet to two rtera: (a) the nal nuber of subsets, and (b) at eah teraton hoosng the subset of axal ardnal. The base dea of the algorth s to aly sequenes of erutatons to eah olete sequene of Ω, n order to obtan ts syetr sequenes. The algorth an start fro any sequene of Ω. When obtanng a syetr sequene that overasses the set Ω, the algorth wll sto and dede that Ω has not the roerty Π. In ths ase, usng the sae dea, t ust be found the axal subset of Ω havng the roerty Π n relaton Ω Θ

5 wth a subset of s(ω). One ay verfy that the roble of arttonng s NP-hard. In the exale below t has been onsdered as otal artton that one orresondng to a nal nuber of reedene grahs. Exale : Let onsder a set of olete sequenes: Ω = = abdegfh, = abdegfh, = abdegfh 4 = abdefgh, 5 = abdegfh Ω = s( ) ( b, ), (, d), ( {, e), ( f, g) 4 abdef ;abdef; abdfe; abdfe; abedf; abedf; Θ = abefd; abefd; abfde; abfde; abfed; abfed Ω Θ Ω has not the roerty Π. The algorth has been arbtrarly started wth =abdegfh. Reark: To obtan syetr sequenes startng wth a ertan sequene eans, n fat, to buld the grah of the syetry relaton, whose onts are the sequenes of Ω and whose edges are labelled by the ars of s(ω). Fgure 5 resents ths onstruton. The otal artton that has been obtaned s: ( ) () = {,, }; = {, }. X ot 4 5 X ot * 4 * * * * * Fg. 5 The grah of the syetry relaton (sequenes overassng Ω are reresented by * ) The obtaned artton: One an verfy that the subset Xot () s equvalent to the ( ) ( ) () ( ) Ω = X ot X ot ; X X ot = ; grah ot G and the grah G s equvalent to the subset ( ) X ot has the roerty Π n relaton wth {, } Xot () (see fgure 6). ( ) X ot has the roerty Π n relaton wth {} = abdegfh G () = ab deg fh X ot a b g f h = abdegfh d e Ω = G 4 = abdefgh b () X ot a d e f g h 5 = abdefgh Fg. 6 Preedene grahs reresentng the set Ω * 6 Conluson In the feld of assebly systes, the reresentaton of a gven set of assebly sequenes by a reedene grah s a ont of nterest. In ths aer, we have analyzed the equvalene between a set of assebly sequenes and a reedene grah. When ths equvalene exsts, we have roved that a roerty of the ntal set of sequenes (roerty Π ) s et. The test of ths roerty an be leented by a sle algorth. For a gven set of assebly sequenes that does not eet the roerty Π, we have suggested a way to obtan an equvalent set of reedene grahs. Obvously, ths roble s NP-hard and, so, any algorth oneved to solve t wll be exonentally olex. Referenes [] S. Ghosh and R.J. Gagnon, A orehensve lterature revew analyss of the desgn, balanng and shedulng of assebly systes, Internatonal Journal of Produton and Researh, Vol.7, No.4, 989, [] D.W. He and A. Kusak, Desgn of Assebly Systes for Modular Produt, IEEE Transatons on Robots and Autoaton, Vol., No.5, 997, [] J.M. Henroud and A. Bourault, LEGA: a outeraded generator of assebly lans, Couter Aded Mehanal Assebly Plannng, Kluwer Aade Publshers, 99 [4] L. S. Hoe de Mello and A. C. Sanderson, A Corret and Colete Algorth for the Generaton of Mehanal Assebly Sequenes, IEEE Transatons

6 on Robots and Autoaton, Vol.7, No., Arl 99, [5] C. Ke and J.M. Henroud, Systeat generaton of assebly reedene grahs, IEEE Inernatonal. Conferene on Robots and Autoaton, Vol., San Dego, Calforna, U.S.A., May 994, [6] V. Mînzu and J.M. Henroud, Assgnent Stohast Algorth n Mult-Produt Assebly Lnes, Proeedngs of the IEEE Internatonal Syosu on Assebly and Task Plannng, Marna Del Rey, Calforna, U.S.A., August 7-9, 997. [7] B. Rekek, E. Falkenauer and A. Delhabre, Mult- Produt Resoure Plannng, Proeedngs of the 997 IEEE Internatonal Syosu On Assebly and Task Plannng, Marna Del Rey, Calforna, U.S.A., August 997,. 5. [8] D.E. Whtney, et al., Couter-Aded Desgn of Flexble Assebly Systes, Frst Reort, C.S. Draer Laboratory, In. Reort No.CSDL 947, Cabrdge, Massahusetts, August 986. [9] D.E. Whtney, et al., Couter-Aded Desgn of Flexble Assebly Systes, Fnal Reort, C.S. Draer Laboratory, In. Reort No.CSDL -R-0, Cabrdge, Massahusetts, U.S.A., January 988.

On the Block-cut Transformation Graphs

On the Block-cut Transformation Graphs Journal of Couter and Matheatal Senes, Vol.66,354-36, June 015 An Internatonal Researh Journal, www.oath-ournal.org ISSN 0976-577 Prnt ISSN 319-8133 Onlne On the Blok-ut Transforaton Grahs B. Basaanagoud

More information

An Economic Analysis of Interconnection Arrangements between Internet Backbone Providers

An Economic Analysis of Interconnection Arrangements between Internet Backbone Providers ONLINE SUPPLEMENT TO An Eonom Analyss of Interonneton Arrangements between Internet Bakbone Provders Yong Tan Unversty of Washngton Busness Shool Box 353 Seattle Washngton 9895-3 ytan@uwashngtonedu I Robert

More information

The vertical differentiation model in the insurance market

The vertical differentiation model in the insurance market The vertal dfferentaton model n the nsurane market Mahto Okura * bstrat Ths note exlores the vertal dfferentaton model n the nsurane market. The man results are as follows. Frst, the eulbrum re dfferental

More information

Bayes Nets Representing and Reasoning about Uncertainty (Continued)

Bayes Nets Representing and Reasoning about Uncertainty (Continued) Bayes Nets Representng and Reasonng about Uncertanty ontnued) obnng the wo Eaples I a at work y neghbor John calls to say that y alar went off y neghbor Mary doesn t call. Soetes the alar s set off by

More information

Understanding Annuities. Some Algebraic Terminology.

Understanding Annuities. Some Algebraic Terminology. Understandng Annutes Ma 162 Sprng 2010 Ma 162 Sprng 2010 March 22, 2010 Some Algebrac Termnology We recall some terms and calculatons from elementary algebra A fnte sequence of numbers s a functon of natural

More information

Generalized Löb s Theorem. Strong Reflection Principles and Large Cardinal Axioms

Generalized Löb s Theorem. Strong Reflection Principles and Large Cardinal Axioms Advanes n Pure athemats 013 3 368-373 http://dxdoorg/10436/apm01333053 Publshed Onlne ay 013 (http://wwwsrporg/journal/apm) Generalzed Löb s eorem Strong Refleton Prnples and Large Cardnal Axoms J Foukzon

More information

15-451/651: Design & Analysis of Algorithms January 22, 2019 Lecture #3: Amortized Analysis last changed: January 18, 2019

15-451/651: Design & Analysis of Algorithms January 22, 2019 Lecture #3: Amortized Analysis last changed: January 18, 2019 5-45/65: Desgn & Analyss of Algorthms January, 09 Lecture #3: Amortzed Analyss last changed: January 8, 09 Introducton In ths lecture we dscuss a useful form of analyss, called amortzed analyss, for problems

More information

UNIVERSITY OF NOTTINGHAM. Discussion Papers in Economics BERTRAND AND COURNOT COMPETITIONS IN A DYNAMIC GAME

UNIVERSITY OF NOTTINGHAM. Discussion Papers in Economics BERTRAND AND COURNOT COMPETITIONS IN A DYNAMIC GAME UNIVERSITY OF NOTTINGHAM Dsusson Paers n Eonoms Dsusson Paer No. 03/06 BERTRAND AND COURNOT COMPETITIONS IN A DYNAMIC GAME y Arjt Mukherjee Arl 003 DP 03/06 ISSN 360-438 UNIVERSITY OF NOTTINGHAM Dsusson

More information

An inductive proof for a closed form formula in truncated inverse sampling

An inductive proof for a closed form formula in truncated inverse sampling Journal of Proagatons n Probablty and Statstcs Vol. No. August Internatonal ed.. 7- An nductve roof for a closed for forula n truncated nverse salng Kuang-Chao Chang Fu Jen Catholc Unversty Abstract Inverse

More information

Parallel Prefix addition

Parallel Prefix addition Marcelo Kryger Sudent ID 015629850 Parallel Prefx addton The parallel prefx adder presented next, performs the addton of two bnary numbers n tme of complexty O(log n) and lnear cost O(n). Lets notce the

More information

Concepts: simple interest, compound interest, annual percentage yield, compounding continuously, mortgages

Concepts: simple interest, compound interest, annual percentage yield, compounding continuously, mortgages Precalculus: Matheatcs of Fnance Concepts: sple nterest, copound nterest, annual percentage yeld, copoundng contnuously, ortgages Note: These topcs are all dscussed n the text, but I a usng slghtly dfferent

More information

Problem Set 6 Finance 1,

Problem Set 6 Finance 1, Carnege Mellon Unversty Graduate School of Industral Admnstraton Chrs Telmer Wnter 2006 Problem Set 6 Fnance, 47-720. (representatve agent constructon) Consder the followng two-perod, two-agent economy.

More information

Appendix for Solving Asset Pricing Models when the Price-Dividend Function is Analytic

Appendix for Solving Asset Pricing Models when the Price-Dividend Function is Analytic Appendx for Solvng Asset Prcng Models when the Prce-Dvdend Functon s Analytc Ovdu L. Caln Yu Chen Thomas F. Cosmano and Alex A. Hmonas January 3, 5 Ths appendx provdes proofs of some results stated n our

More information

Linear Combinations of Random Variables and Sampling (100 points)

Linear Combinations of Random Variables and Sampling (100 points) Economcs 30330: Statstcs for Economcs Problem Set 6 Unversty of Notre Dame Instructor: Julo Garín Sprng 2012 Lnear Combnatons of Random Varables and Samplng 100 ponts 1. Four-part problem. Go get some

More information

In this appendix, we present some theoretical aspects of game theory that would be followed by players in a restructured energy market.

In this appendix, we present some theoretical aspects of game theory that would be followed by players in a restructured energy market. Market Operatons n Electrc Power Systes: Forecastng, Schedulng, and Rsk Manageentg Mohaad Shahdehpour, Hat Yan, Zuy L Copyrght 2002 John Wley & Sons, Inc. ISBNs: 0-47-44337-9 (Hardback); 0-47-2242-X (Electronc)

More information

Production and Supply Chain Management Logistics. Paolo Detti Department of Information Engeneering and Mathematical Sciences University of Siena

Production and Supply Chain Management Logistics. Paolo Detti Department of Information Engeneering and Mathematical Sciences University of Siena Producton and Supply Chan Management Logstcs Paolo Dett Department of Informaton Engeneerng and Mathematcal Scences Unversty of Sena Convergence and complexty of the algorthm Convergence of the algorthm

More information

Modified Vogel s Approximation Method For Solving Transportation Problems

Modified Vogel s Approximation Method For Solving Transportation Problems Modfed Vogel s pproxaton Method For Solvng Transportaton Probles bdl Sattar Sooro 1 Mhaad Jnad Grdeo nand Tlara 3 dr_sattarsooro@yahoo.co.n haadnad.rapt@yahoo.co,,a.tlara@grffth.ed.a 1 Professor of Matheatcs,

More information

Homework 9: due Monday, 27 October, 2008

Homework 9: due Monday, 27 October, 2008 PROBLEM ONE Homework 9: due Monday, 7 October, 008. (Exercses from the book, 6 th edton, 6.6, -3.) Determne the number of dstnct orderngs of the letters gven: (a) GUIDE (b) SCHOOL (c) SALESPERSONS. (Exercses

More information

A New P2P Network Routing Algorithm Based on ISODATA Clustering Topology

A New P2P Network Routing Algorithm Based on ISODATA Clustering Topology Avalable onlne at www.senedret.o Proeda Engneerng 5 (20) 2966 2970 Advaned n Control Engneerngand Inforaton Sene A ew P2P etwork Routng Algorth Based on ISODATA Clusterng Topology Y Ma a, Zhenhua Tan a,

More information

Single-Item Auctions. CS 234r: Markets for Networks and Crowds Lecture 4 Auctions, Mechanisms, and Welfare Maximization

Single-Item Auctions. CS 234r: Markets for Networks and Crowds Lecture 4 Auctions, Mechanisms, and Welfare Maximization CS 234r: Markets for Networks and Crowds Lecture 4 Auctons, Mechansms, and Welfare Maxmzaton Sngle-Item Auctons Suppose we have one or more tems to sell and a pool of potental buyers. How should we decde

More information

EDC Introduction

EDC Introduction .0 Introducton EDC3 In the last set of notes (EDC), we saw how to use penalty factors n solvng the EDC problem wth losses. In ths set of notes, we want to address two closely related ssues. What are, exactly,

More information

Survey of Math: Chapter 22: Consumer Finance Borrowing Page 1

Survey of Math: Chapter 22: Consumer Finance Borrowing Page 1 Survey of Math: Chapter 22: Consumer Fnance Borrowng Page 1 APR and EAR Borrowng s savng looked at from a dfferent perspectve. The dea of smple nterest and compound nterest stll apply. A new term s the

More information

Finance 402: Problem Set 1 Solutions

Finance 402: Problem Set 1 Solutions Fnance 402: Problem Set 1 Solutons Note: Where approprate, the fnal answer for each problem s gven n bold talcs for those not nterested n the dscusson of the soluton. 1. The annual coupon rate s 6%. A

More information

Data Mining Linear and Logistic Regression

Data Mining Linear and Logistic Regression 07/02/207 Data Mnng Lnear and Logstc Regresson Mchael L of 26 Regresson In statstcal modellng, regresson analyss s a statstcal process for estmatng the relatonshps among varables. Regresson models are

More information

Finite Math - Fall Section Future Value of an Annuity; Sinking Funds

Finite Math - Fall Section Future Value of an Annuity; Sinking Funds Fnte Math - Fall 2016 Lecture Notes - 9/19/2016 Secton 3.3 - Future Value of an Annuty; Snkng Funds Snkng Funds. We can turn the annutes pcture around and ask how much we would need to depost nto an account

More information

ECE 586GT: Problem Set 2: Problems and Solutions Uniqueness of Nash equilibria, zero sum games, evolutionary dynamics

ECE 586GT: Problem Set 2: Problems and Solutions Uniqueness of Nash equilibria, zero sum games, evolutionary dynamics Unversty of Illnos Fall 08 ECE 586GT: Problem Set : Problems and Solutons Unqueness of Nash equlbra, zero sum games, evolutonary dynamcs Due: Tuesday, Sept. 5, at begnnng of class Readng: Course notes,

More information

OPERATIONS RESEARCH. Game Theory

OPERATIONS RESEARCH. Game Theory OPERATIONS RESEARCH Chapter 2 Game Theory Prof. Bbhas C. Gr Department of Mathematcs Jadavpur Unversty Kolkata, Inda Emal: bcgr.umath@gmal.com 1.0 Introducton Game theory was developed for decson makng

More information

New Distance Measures on Dual Hesitant Fuzzy Sets and Their Application in Pattern Recognition

New Distance Measures on Dual Hesitant Fuzzy Sets and Their Application in Pattern Recognition Journal of Artfcal Intellgence Practce (206) : 8-3 Clausus Scentfc Press, Canada New Dstance Measures on Dual Hestant Fuzzy Sets and Ther Applcaton n Pattern Recognton L Xn a, Zhang Xaohong* b College

More information

Problems to be discussed at the 5 th seminar Suggested solutions

Problems to be discussed at the 5 th seminar Suggested solutions ECON4260 Behavoral Economcs Problems to be dscussed at the 5 th semnar Suggested solutons Problem 1 a) Consder an ultmatum game n whch the proposer gets, ntally, 100 NOK. Assume that both the proposer

More information

II. Random Variables. Variable Types. Variables Map Outcomes to Numbers

II. Random Variables. Variable Types. Variables Map Outcomes to Numbers II. Random Varables Random varables operate n much the same way as the outcomes or events n some arbtrary sample space the dstncton s that random varables are smply outcomes that are represented numercally.

More information

Elton, Gruber, Brown, and Goetzmann. Modern Portfolio Theory and Investment Analysis, 7th Edition. Solutions to Text Problems: Chapter 9

Elton, Gruber, Brown, and Goetzmann. Modern Portfolio Theory and Investment Analysis, 7th Edition. Solutions to Text Problems: Chapter 9 Elton, Gruber, Brown, and Goetzmann Modern Portfolo Theory and Investment Analyss, 7th Edton Solutons to Text Problems: Chapter 9 Chapter 9: Problem In the table below, gven that the rskless rate equals

More information

-~~?.~~.!.i.':':'.~.~-~-~~~~':':'.~~~.::.~~~~~~~--~-~-~~.::."!}.~!.~.. ~.~~-~...

-~~?.~~.!.i.':':'.~.~-~-~~~~':':'.~~~.::.~~~~~~~--~-~-~~.::.!}.~!.~.. ~.~~-~... -~~?.~~.!..':':'.~.~-~-~~~~':':'.~~~.::.~~~~~~~--~-~-~~.::."!}.~!.~.. ~.~~-~.... Part 1: Defnng schedules (10 Descrbe the followng terms as used n schedulng projects. 1.1 Crtcal path 1.2 Slack tme or float

More information

Enhancment of Inventory Management Approaches in Vehicle Routing-Cross Docking Problems

Enhancment of Inventory Management Approaches in Vehicle Routing-Cross Docking Problems Enhanment of Inventory Management Approahes n Vehle Routng-Cross Dong Problems Mahd Alnaghan*, Hamed Amanpour*, Erfan Babaee rolaee* *Department of Industral and Systems Engneerng, Isfahan Unversty of

More information

Chapter - IV. Total and Middle Fuzzy Graph

Chapter - IV. Total and Middle Fuzzy Graph Chapter - IV otal and Mddle Fuzzy Graph CHAPER - IV OAL AND MIDDLE FUZZY GRAPH In ths chapter for the gven fuzzy graph G:(σ, µ), subdvson fuzzy graph sd(g) : ( σ sd, µ sd ), square fuzzy graph S 2 ( G)

More information

Equilibrium in Prediction Markets with Buyers and Sellers

Equilibrium in Prediction Markets with Buyers and Sellers Equlbrum n Predcton Markets wth Buyers and Sellers Shpra Agrawal Nmrod Megddo Benamn Armbruster Abstract Predcton markets wth buyers and sellers of contracts on multple outcomes are shown to have unque

More information

Elements of Economic Analysis II Lecture VI: Industry Supply

Elements of Economic Analysis II Lecture VI: Industry Supply Elements of Economc Analyss II Lecture VI: Industry Supply Ka Hao Yang 10/12/2017 In the prevous lecture, we analyzed the frm s supply decson usng a set of smple graphcal analyses. In fact, the dscusson

More information

Physics 4A. Error Analysis or Experimental Uncertainty. Error

Physics 4A. Error Analysis or Experimental Uncertainty. Error Physcs 4A Error Analyss or Expermental Uncertanty Slde Slde 2 Slde 3 Slde 4 Slde 5 Slde 6 Slde 7 Slde 8 Slde 9 Slde 0 Slde Slde 2 Slde 3 Slde 4 Slde 5 Slde 6 Slde 7 Slde 8 Slde 9 Slde 20 Slde 2 Error n

More information

Study on Trade Restrictiveness of Agricultural Policies in Iran

Study on Trade Restrictiveness of Agricultural Policies in Iran Internatonal Journal of Agrultural Sene and Researh Volume, Number 1, Wnter 011(Seral #) Study on Trade Restrtveness of Agrultural Poles n Iran G. rouz 1 *; R. Moghaddas 1 ; S. Yazdan 1: Department of

More information

COS 511: Theoretical Machine Learning. Lecturer: Rob Schapire Lecture #21 Scribe: Lawrence Diao April 23, 2013

COS 511: Theoretical Machine Learning. Lecturer: Rob Schapire Lecture #21 Scribe: Lawrence Diao April 23, 2013 COS 511: Theoretcal Machne Learnng Lecturer: Rob Schapre Lecture #21 Scrbe: Lawrence Dao Aprl 23, 2013 1 On-Lne Log Loss To recap the end of the last lecture, we have the followng on-lne problem wth N

More information

MULTIPLE CURVE CONSTRUCTION

MULTIPLE CURVE CONSTRUCTION MULTIPLE CURVE CONSTRUCTION RICHARD WHITE 1. Introducton In the post-credt-crunch world, swaps are generally collateralzed under a ISDA Master Agreement Andersen and Pterbarg p266, wth collateral rates

More information

Lecture Note 2 Time Value of Money

Lecture Note 2 Time Value of Money Seg250 Management Prncples for Engneerng Managers Lecture ote 2 Tme Value of Money Department of Systems Engneerng and Engneerng Management The Chnese Unversty of Hong Kong Interest: The Cost of Money

More information

Parsing beyond context-free grammar: Tree Adjoining Grammar Parsing I

Parsing beyond context-free grammar: Tree Adjoining Grammar Parsing I Parsng beyond context-free grammar: Tree donng Grammar Parsng I Laura Kallmeyer, Wolfgang Maer ommersemester 2009 duncton and substtuton (1) Tree donng Grammars (TG) Josh et al. (1975), Josh & chabes (1997):

More information

Appendix - Normally Distributed Admissible Choices are Optimal

Appendix - Normally Distributed Admissible Choices are Optimal Appendx - Normally Dstrbuted Admssble Choces are Optmal James N. Bodurtha, Jr. McDonough School of Busness Georgetown Unversty and Q Shen Stafford Partners Aprl 994 latest revson September 00 Abstract

More information

occurrence of a larger storm than our culvert or bridge is barely capable of handling? (what is The main question is: What is the possibility of

occurrence of a larger storm than our culvert or bridge is barely capable of handling? (what is The main question is: What is the possibility of Module 8: Probablty and Statstcal Methods n Water Resources Engneerng Bob Ptt Unversty of Alabama Tuscaloosa, AL Flow data are avalable from numerous USGS operated flow recordng statons. Data s usually

More information

The Effect of Market Structure and Conduct on the Incentive for a Horizontal Merger

The Effect of Market Structure and Conduct on the Incentive for a Horizontal Merger Volue 5, Nuber, June 000 The Effect of Market Structure and Conduct on the Incentve for a Horzontal Merger Hyukseung Shn In ths paper, we exane how arket structure and frs conduct affect the prvate ncentve

More information

ECO 209Y MACROECONOMIC THEORY AND POLICY LECTURE 8: THE OPEN ECONOMY WITH FIXED EXCHANGE RATES

ECO 209Y MACROECONOMIC THEORY AND POLICY LECTURE 8: THE OPEN ECONOMY WITH FIXED EXCHANGE RATES ECO 209 MACROECONOMIC THEOR AND POLIC LECTURE 8: THE OPEN ECONOM WITH FIXED EXCHANGE RATES Gustavo Indart Slde 1 OPEN ECONOM UNDER FIXED EXCHANGE RATES Let s consder an open economy wth no captal moblty

More information

TCOM501 Networking: Theory & Fundamentals Final Examination Professor Yannis A. Korilis April 26, 2002

TCOM501 Networking: Theory & Fundamentals Final Examination Professor Yannis A. Korilis April 26, 2002 TO5 Networng: Theory & undamentals nal xamnaton Professor Yanns. orls prl, Problem [ ponts]: onsder a rng networ wth nodes,,,. In ths networ, a customer that completes servce at node exts the networ wth

More information

To find a non-split strong dominating set of an interval graph using an algorithm

To find a non-split strong dominating set of an interval graph using an algorithm IOSR Journal of Mathematcs (IOSR-JM) e-issn: 2278-5728,p-ISSN: 219-765X, Volume 6, Issue 2 (Mar - Apr 201), PP 05-10 To fnd a non-splt rong domnatng set of an nterval graph usng an algorthm Dr A Sudhakaraah*,

More information

Tests for Two Correlations

Tests for Two Correlations PASS Sample Sze Software Chapter 805 Tests for Two Correlatons Introducton The correlaton coeffcent (or correlaton), ρ, s a popular parameter for descrbng the strength of the assocaton between two varables.

More information

Measures of Spread IQR and Deviation. For exam X, calculate the mean, median and mode. For exam Y, calculate the mean, median and mode.

Measures of Spread IQR and Deviation. For exam X, calculate the mean, median and mode. For exam Y, calculate the mean, median and mode. Part 4 Measures of Spread IQR and Devaton In Part we learned how the three measures of center offer dfferent ways of provdng us wth a sngle representatve value for a data set. However, consder the followng

More information

3: Central Limit Theorem, Systematic Errors

3: Central Limit Theorem, Systematic Errors 3: Central Lmt Theorem, Systematc Errors 1 Errors 1.1 Central Lmt Theorem Ths theorem s of prme mportance when measurng physcal quanttes because usually the mperfectons n the measurements are due to several

More information

Fast Laplacian Solvers by Sparsification

Fast Laplacian Solvers by Sparsification Spectral Graph Theory Lecture 19 Fast Laplacan Solvers by Sparsfcaton Danel A. Spelman November 9, 2015 Dsclamer These notes are not necessarly an accurate representaton of what happened n class. The notes

More information

Financial mathematics

Financial mathematics Fnancal mathematcs Jean-Luc Bouchot jean-luc.bouchot@drexel.edu February 19, 2013 Warnng Ths s a work n progress. I can not ensure t to be mstake free at the moment. It s also lackng some nformaton. But

More information

Hewlett Packard 10BII Calculator

Hewlett Packard 10BII Calculator Hewlett Packard 0BII Calculator Keystrokes for the HP 0BII are shown n the tet. However, takng a mnute to revew the Quk Start secton, below, wll be very helpful n gettng started wth your calculator. Note:

More information

FORD MOTOR CREDIT COMPANY SUGGESTED ANSWERS. Richard M. Levich. New York University Stern School of Business. Revised, February 1999

FORD MOTOR CREDIT COMPANY SUGGESTED ANSWERS. Richard M. Levich. New York University Stern School of Business. Revised, February 1999 FORD MOTOR CREDIT COMPANY SUGGESTED ANSWERS by Rchard M. Levch New York Unversty Stern School of Busness Revsed, February 1999 1 SETTING UP THE PROBLEM The bond s beng sold to Swss nvestors for a prce

More information

Hedging Greeks for a portfolio of options using linear and quadratic programming

Hedging Greeks for a portfolio of options using linear and quadratic programming MPRA Munch Personal RePEc Archve Hedgng reeks for a of otons usng lnear and quadratc rogrammng Panka Snha and Archt Johar Faculty of Management Studes, Unversty of elh, elh 5. February 200 Onlne at htt://mra.ub.un-muenchen.de/20834/

More information

Analysis of adiabatic heating in high strain rate torsion tests by an iterative method: application to an ultrahigh carbon steel

Analysis of adiabatic heating in high strain rate torsion tests by an iterative method: application to an ultrahigh carbon steel Comutatonal Methods and Exerments n Materals Charatersaton III 219 Analyss of adabat heatng n hgh stran rate torson tests by an teratve method: alaton to an ultrahgh arbon steel J. Castellanos 1, I. Rero

More information

Inference on Reliability in the Gamma and Inverted Gamma Distributions

Inference on Reliability in the Gamma and Inverted Gamma Distributions Statstcs n the Twenty-Frst Century: Specal Volue In Honour of Dstngushed Professor Dr. Mr Masoo Al On the Occason of hs 75th Brthday Annversary PJSOR, Vol. 8, No. 3, pages 635-643, July Jungsoo Woo Departent

More information

Labor Market Transitions in Peru

Labor Market Transitions in Peru Labor Market Transtons n Peru Javer Herrera* Davd Rosas Shady** *IRD and INEI, E-mal: jherrera@ne.gob.pe ** IADB, E-mal: davdro@adb.org The Issue U s one of the major ssues n Peru However: - The U rate

More information

Evaluation of Investment Risk of Solar Power Projects Based on Improved TOPSIS Model

Evaluation of Investment Risk of Solar Power Projects Based on Improved TOPSIS Model ounatons n Inforaton Sene and Manageent Engneerng Evaluaton of Investent Rsk of Solar Power Proets Based on Iproved TOPSIS Model Yunna Wu, Lngshuang Xu, Xnlang Hu Shool of Eonos and Manageent, North hna

More information

- contrast so-called first-best outcome of Lindahl equilibrium with case of private provision through voluntary contributions of households

- contrast so-called first-best outcome of Lindahl equilibrium with case of private provision through voluntary contributions of households Prvate Provson - contrast so-called frst-best outcome of Lndahl equlbrum wth case of prvate provson through voluntary contrbutons of households - need to make an assumpton about how each household expects

More information

arxiv: v2 [math.co] 6 Apr 2016

arxiv: v2 [math.co] 6 Apr 2016 On the number of equvalence classes of nvertble Boolean functons under acton of permutaton of varables on doman and range arxv:1603.04386v2 [math.co] 6 Apr 2016 Marko Carć and Modrag Žvkovć Abstract. Let

More information

Price and Quantity Competition Revisited. Abstract

Price and Quantity Competition Revisited. Abstract rce and uantty Competton Revsted X. Henry Wang Unversty of Mssour - Columba Abstract By enlargng the parameter space orgnally consdered by Sngh and Vves (984 to allow for a wder range of cost asymmetry,

More information

Macroeconomic Theory and Policy

Macroeconomic Theory and Policy ECO 209 Macroeconomc Theory and Polcy Lecture 7: The Open Economy wth Fxed Exchange Rates Gustavo Indart Slde 1 Open Economy under Fxed Exchange Rates Let s consder an open economy wth no captal moblty

More information

Jean-Paul Murara, Västeras, 26-April Mälardalen University, Sweden. Pricing EO under 2-dim. B S PDE by. using the Crank-Nicolson Method

Jean-Paul Murara, Västeras, 26-April Mälardalen University, Sweden. Pricing EO under 2-dim. B S PDE by. using the Crank-Nicolson Method Prcng EO under Mälardalen Unversty, Sweden Västeras, 26-Aprl-2017 1 / 15 Outlne 1 2 3 2 / 15 Optons - contracts that gve to the holder the rght but not the oblgaton to buy/sell an asset sometmes n the

More information

Sensitivity of health-related scales is a non-decreasing function of

Sensitivity of health-related scales is a non-decreasing function of Senstvty of health-related sales s a non-dereasng funton of ther lasses. Vasleos Maroulas and Demosthenes B. Panagotaos 2,* Insttute for Mathemats and ts Applatons, Unversty of Mnnesota, Mnneapols, USA.

More information

Macroeconomic Theory and Policy

Macroeconomic Theory and Policy ECO 209 Macroeconomc Theory and Polcy Lecture 7: The Open Economy wth Fxed Exchange Rates Gustavo Indart Slde 1 Open Economy under Fxed Exchange Rates Let s consder an open economy wth no captal moblty

More information

Keele Economics Research Papers

Keele Economics Research Papers KERP 00/0 Innovaton Lensng and Welfare Art Mukheree Keele Eonoms Researh Paers Keele February 00 KERP Keele Eonoms Researh Paers The Keele Eonoms Deartment rodues ths seres of researh aers n order to stmulate

More information

Floorplanning Algorithm for multiple clock domains

Floorplanning Algorithm for multiple clock domains Proceedngs of the 4th WSEASIASME Int Conf on System Scence and Smulaton n Engneerng, Tenerfe, San, December 16-18, 005 (156-16 Floorlannng Algorthm for multle domans Changhong Zhao, Jan Chen, Dan Zhou,

More information

STRATEGY CHOICE IN TOURISM SUPPLY CHAINS FOR PACKAGE HOLIDAYS: A GAME-THEORETIC APPROACH

STRATEGY CHOICE IN TOURISM SUPPLY CHAINS FOR PACKAGE HOLIDAYS: A GAME-THEORETIC APPROACH Unversty of Massahusetts Amherst SholarWorks@UMass Amherst Toursm Travel and esearh Assoaton: Advanng Toursm esearh Globally 007 ttra Internatonal Conferene STATEGY CHOICE I UISM SULY CIS FO ACKAGE HOLIDAYS:

More information

Economic Design of Short-Run CSP-1 Plan Under Linear Inspection Cost

Economic Design of Short-Run CSP-1 Plan Under Linear Inspection Cost Tamkang Journal of Scence and Engneerng, Vol. 9, No 1, pp. 19 23 (2006) 19 Economc Desgn of Short-Run CSP-1 Plan Under Lnear Inspecton Cost Chung-Ho Chen 1 * and Chao-Yu Chou 2 1 Department of Industral

More information

Multifactor Term Structure Models

Multifactor Term Structure Models 1 Multfactor Term Structure Models A. Lmtatons of One-Factor Models 1. Returns on bonds of all maturtes are perfectly correlated. 2. Term structure (and prces of every other dervatves) are unquely determned

More information

Fall 2017 Social Sciences 7418 University of Wisconsin-Madison Problem Set 3 Answers

Fall 2017 Social Sciences 7418 University of Wisconsin-Madison Problem Set 3 Answers ublc Affars 854 enze D. Chnn Fall 07 Socal Scences 748 Unversty of Wsconsn-adson roblem Set 3 Answers Due n Lecture on Wednesday, November st. " Box n" your answers to the algebrac questons.. Fscal polcy

More information

2) In the medium-run/long-run, a decrease in the budget deficit will produce:

2) In the medium-run/long-run, a decrease in the budget deficit will produce: 4.02 Quz 2 Solutons Fall 2004 Multple-Choce Questons ) Consder the wage-settng and prce-settng equatons we studed n class. Suppose the markup, µ, equals 0.25, and F(u,z) = -u. What s the natural rate of

More information

The economics of climate change

The economics of climate change The Economcs of Clmate Change C 175 The economcs of clmate change C 175 Chrstan Traeger Part 2: Effcency, Publc Goods, Externaltes Suggested background readng for emergng questons: olstad, Charles D. (2000),

More information

ENHANCING BASEL METHOD VIA CONDITIONAL DISTRIBUTIONS THAT CAPTURE STRONGER CONNECTION AMONG CREDIT LOSSES IN DOWNTURNS

ENHANCING BASEL METHOD VIA CONDITIONAL DISTRIBUTIONS THAT CAPTURE STRONGER CONNECTION AMONG CREDIT LOSSES IN DOWNTURNS ENHANCING BASEL METHOD VIA CONDITIONAL DISTRIBUTIONS THAT CAPTURE STRONGER CONNECTION AMONG CREDIT LOSSES IN DOWNTURNS Fernando F. Morera Credt Researh Centre, Unversty of Ednburgh Emal: F.F.Morera@sms.ed.a.uk

More information

YORK UNIVERSITY Faculty of Science Department of Mathematics and Statistics MATH A Test #2 November 03, 2014

YORK UNIVERSITY Faculty of Science Department of Mathematics and Statistics MATH A Test #2 November 03, 2014 Famly Name prnt): YORK UNIVERSITY Faculty of Scence Department of Mathematcs and Statstcs MATH 2280.00 A Test #2 November 0, 2014 Solutons Gven Name: Student No: Sgnature: INSTRUCTIONS: 1. Please wrte

More information

Strategic Dynamic Sourcing from Competing Suppliers with Transferable Capacity Investment

Strategic Dynamic Sourcing from Competing Suppliers with Transferable Capacity Investment Strateg Dynam Sourng from Competng Supplers wth Transferable Capaty nvestment Cuhong L Laurens G. Debo Shool of Busness, Unversty of Connetut, Storrs, CT 0669 The Booth Shool of Busness, Unversty of Chago,

More information

Project Management Project Phases the S curve

Project Management Project Phases the S curve Project lfe cycle and resource usage Phases Project Management Project Phases the S curve Eng. Gorgo Locatell RATE OF RESOURCE ES Conceptual Defnton Realzaton Release TIME Cumulated resource usage and

More information

Collective Motion from Consensus with Cartesian Coordinate Coupling - Part II: Double-integrator Dynamics

Collective Motion from Consensus with Cartesian Coordinate Coupling - Part II: Double-integrator Dynamics Proceedngs of the 47th IEEE Conference on Decson Control Cancun Mexco Dec. 9-8 TuB. Collectve Moton from Consensus wth Cartesan Coordnate Couplng - Part II: Double-ntegrator Dynamcs We Ren Abstract Ths

More information

Elton, Gruber, Brown, and Goetzmann. Modern Portfolio Theory and Investment Analysis, 7th Edition. Solutions to Text Problems: Chapter 16

Elton, Gruber, Brown, and Goetzmann. Modern Portfolio Theory and Investment Analysis, 7th Edition. Solutions to Text Problems: Chapter 16 lton, Gruer, rown, and Goetzmann Modern Portfolo Theory and Investment nalyss, 7th dton Solutons to Text Prolems: hapter 6 hapter 6: Prolem From the text we know that three ponts determne a plane. The

More information

A DUAL EXTERIOR POINT SIMPLEX TYPE ALGORITHM FOR THE MINIMUM COST NETWORK FLOW PROBLEM

A DUAL EXTERIOR POINT SIMPLEX TYPE ALGORITHM FOR THE MINIMUM COST NETWORK FLOW PROBLEM Yugoslav Journal of Operatons Research Vol 19 (2009), Number 1, 157-170 DOI:10.2298/YUJOR0901157G A DUAL EXTERIOR POINT SIMPLEX TYPE ALGORITHM FOR THE MINIMUM COST NETWORK FLOW PROBLEM George GERANIS Konstantnos

More information

Two-Settlement Electricity Markets with Price Caps and Cournot Generation Firms

Two-Settlement Electricity Markets with Price Caps and Cournot Generation Firms Two-Settlement Eletrty Markets wth Pre Caps and Cournot Generaton Frms Jan Yao, Shmuel S. Oren, Ilan Adler Department of Industral Engneerng and Operatons Researh 4141 Etheverry Hall, Unversty of Calforna

More information

COFUNDS PENSION ACCOUNT TRANSFER REQUEST FORM for existing clients

COFUNDS PENSION ACCOUNT TRANSFER REQUEST FORM for existing clients COFUNDS PENSION ACCOUNT TRANSFER REQUEST FORM for exstng clents Also avalable on the Aegon webste: Cofunds Penson Account Drawdown Transfer Request Form transfer a penson plan from whch full or partal

More information

MODELING THE OBSOLESCENCE OF CRITICAL HUMAN SKILLS NECESSARY FOR SUPPORTING LEGACY SYSTEMS

MODELING THE OBSOLESCENCE OF CRITICAL HUMAN SKILLS NECESSARY FOR SUPPORTING LEGACY SYSTEMS Proceedngs of the ASM 212 Internatonal Desgn ngneerng Techncal Conferences & Couters and Inforaton n ngneerng Conference DFMLC 212 August 12-15, 212, Chcago, IL, USA DTC212-71554 MODLING TH OBSOLSCNC OF

More information

Games and Decisions. Part I: Basic Theorems. Contents. 1 Introduction. Jane Yuxin Wang. 1 Introduction 1. 2 Two-player Games 2

Games and Decisions. Part I: Basic Theorems. Contents. 1 Introduction. Jane Yuxin Wang. 1 Introduction 1. 2 Two-player Games 2 Games and Decsons Part I: Basc Theorems Jane Yuxn Wang Contents 1 Introducton 1 2 Two-player Games 2 2.1 Zero-sum Games................................ 3 2.1.1 Pure Strateges.............................

More information

Quiz on Deterministic part of course October 22, 2002

Quiz on Deterministic part of course October 22, 2002 Engneerng ystems Analyss for Desgn Quz on Determnstc part of course October 22, 2002 Ths s a closed book exercse. You may use calculators Grade Tables There are 90 ponts possble for the regular test, or

More information

SUPPLEMENT TO BOOTSTRAPPING REALIZED VOLATILITY (Econometrica, Vol. 77, No. 1, January, 2009, )

SUPPLEMENT TO BOOTSTRAPPING REALIZED VOLATILITY (Econometrica, Vol. 77, No. 1, January, 2009, ) Econometrca Supplementary Materal SUPPLEMENT TO BOOTSTRAPPING REALIZED VOLATILITY Econometrca, Vol. 77, No. 1, January, 009, 83 306 BY SÍLVIA GONÇALVES AND NOUR MEDDAHI THIS SUPPLEMENT IS ORGANIZED asfollows.frst,wentroducesomenotaton.

More information

Lecture 33: Rutherford s Formula, and Rocket Motion

Lecture 33: Rutherford s Formula, and Rocket Motion Lecture 33: Rutherrd s Frula, and Rcket Mtn Fr gravty and the electrc rce, S we have: U( r) Nte that we can deterne r n by ndng the dstance at whch the ttal energy equals the eectve ptental Ths ntegral

More information

TOTAL CURVATURES OF A CLOSED CURVE IN EUCLIDEAN n-space

TOTAL CURVATURES OF A CLOSED CURVE IN EUCLIDEAN n-space PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY Volume 132, Number 7, Pages 2127 2132 S 0002-9939(04)07310-1 Artcle electroncally ublshed on January 23, 2004 TOTAL CURVATURES OF A CLOSED CURVE IN EUCLIDEAN

More information

UNIVERSITY OF NOTTINGHAM

UNIVERSITY OF NOTTINGHAM UNIVERSITY OF NOTTINGHAM SCHOOL OF ECONOMICS DISCUSSION PAPER 99/28 Welfare Analyss n a Cournot Game wth a Publc Good by Indraneel Dasgupta School of Economcs, Unversty of Nottngham, Nottngham NG7 2RD,

More information

Fall 2016 Social Sciences 7418 University of Wisconsin-Madison. Transactions and Portfolio Crowding Out

Fall 2016 Social Sciences 7418 University of Wisconsin-Madison. Transactions and Portfolio Crowding Out Economcs 435 Menze D. Cnn Fall 6 Socal Scences 748 Unversty of Wsconsn-Madson. Standard IS-LM Transactons and ortfolo Crowdng Out Transactons crowdng out of nvestment s te reducton n nvestment attrbutable

More information

Trivial lump sum R5.1

Trivial lump sum R5.1 Trval lump sum R5.1 Optons form Once you have flled n ths form, please return t wth the documents we have requested. You can ether post or emal the form and the documents to us. Premer PO Box 108 BLYTH

More information

The Strategic Role of Public R&D in Agriculture

The Strategic Role of Public R&D in Agriculture The Strate Role of Publ R&D n Arulture Alejandro Onofr Departent of Arultural Eonos Unversty of Nebraska-noln Konstantnos Gannakas Departent of Arultural Eonos Unversty of Nebraska-noln Abstrat - The role

More information

Improvement of Order Promise With Material Constraints and Finite Capacity

Improvement of Order Promise With Material Constraints and Finite Capacity Iproveent of Order Prose Wth Materal Constrants and Fnte Capacty Iproveent of Order Prose Wth Materal Constrants and Fnte Capacty Jun-Han Chen Departent of Industral Engneerng and Manageent, Cheng Shu

More information

Mode is the value which occurs most frequency. The mode may not exist, and even if it does, it may not be unique.

Mode is the value which occurs most frequency. The mode may not exist, and even if it does, it may not be unique. 1.7.4 Mode Mode s the value whch occurs most frequency. The mode may not exst, and even f t does, t may not be unque. For ungrouped data, we smply count the largest frequency of the gven value. If all

More information

PREFERENCE DOMAINS AND THE MONOTONICITY OF CONDORCET EXTENSIONS

PREFERENCE DOMAINS AND THE MONOTONICITY OF CONDORCET EXTENSIONS PREFERECE DOMAIS AD THE MOOTOICITY OF CODORCET EXTESIOS PAUL J. HEALY AD MICHAEL PERESS ABSTRACT. An alternatve s a Condorcet wnner f t beats all other alternatves n a parwse majorty vote. A socal choce

More information

Welfare Aspects in the Realignment of Commercial Framework. between Japan and China

Welfare Aspects in the Realignment of Commercial Framework. between Japan and China Prepared for the 13 th INFORUM World Conference n Huangshan, Chna, July 3 9, 2005 Welfare Aspects n the Realgnment of Commercal Framework between Japan and Chna Toshak Hasegawa Chuo Unversty, Japan Introducton

More information

Tests for Two Ordered Categorical Variables

Tests for Two Ordered Categorical Variables Chapter 253 Tests for Two Ordered Categorcal Varables Introducton Ths module computes power and sample sze for tests of ordered categorcal data such as Lkert scale data. Assumng proportonal odds, such

More information

Consumption Based Asset Pricing

Consumption Based Asset Pricing Consumpton Based Asset Prcng Mchael Bar Aprl 25, 208 Contents Introducton 2 Model 2. Prcng rsk-free asset............................... 3 2.2 Prcng rsky assets................................ 4 2.3 Bubbles......................................

More information