ANALYZING THE RELATIONSHIPS BETWEEN QUALITY, TIME, AND COST IN PROJECT MANAGEMENT DECISION MAKING


 Miles Andrews
 2 years ago
 Views:
Transcription
1 ANALYZING THE RELATIONSHIPS BETWEEN QUALITY, TIME, AND COST IN PROJECT MANAGEMENT DECISION MAKING Matthew J. Lberatore, Department of Management and Operatons, Vllanova Unversty, Vllanova, PA 19085, , Bruce PollackJohnson, Department of Mathematcal Scences, Vllanova Unversty, Vllanova, PA 19085, , ABSTRACT Ths paper presents a mathematcal programmng model that allows qualty to be explctly consdered n project plannng and schedulng, whle addressng the tradeoffs between qualty, tme, and cost. Usng a constructon example we show how ths model can be used to generate qualty level curves to llustrate the tradeoffs among tme, cost, and qualty. These level curves can then be used by project managers to make project schedulng decsons that explctly model and consder qualty as well as tme and cost, so that better and more approprate decsons can be made for a partcular stuaton. Keywords: project management, qualty management, project plannng, project schedulng, mathematcal programmng INTRODUCTION Project management requres achevng cost, schedule, and performance targets, whle provdng an outcome that satsfes the clent. A measure of the value of the project to the clent s the level of qualty assocated wth the completed project. It follows that mportant manageral decsons relate to the level of qualty acheved for each of the project s tasks, snce n toto the qualty of the tasks defnes the qualty of the project. The emphass n project plannng and schedulng has been on the relatonshp between tme and cost, wth lttle attenton drected to qualty. In most stuatons there are alternate approaches for completng each task, each havng ts own tme, cost, and qualty. The manageral queston of nterest relates to these choces, whch have profound mpacts on the project outcome. The purpose of ths paper s to present a modelng framework that allows qualty to be explctly consdered n project plannng and schedulng, whle addressng the tradeoffs between qualty, tme, and cost. Ths paper also offers some manageral nsghts that are derved from the modelng framework through mproved understandng of these choces and tradeoffs. PROJECT QUALITY Qualty can be defned as a dynamc state assocated wth products, servces, people, processes, and envronments that meet or exceed specfcatons [2]. The ISO 9000 defnton of qualty [3] has been adopted by the Project Management Body of Knowledge [7]. Accordng to the PMBOK, qualty must address both the management of the project and the product of the
2 project. Our nterest n qualty relates to the qualty plannng process, and addresses qualty at the task and overall project levels. Paqun et al. [5] contend that a method for assessng qualty must enable project managers to elucdate and structure the clent s needs and expectatons. We are nterested n measurng planned qualty of work for dfferent desgns of specfc actvtes usng such a method. We assume that there are choces for completng tasks that vary n qualty, tme, and cost. The suggested approach requres the dentfcaton of the qualty attrbutes that are relevant for the project. An example usng the Analytc Herarchy Process (AHP) [8] [9] to evaluate the qualty of a task opton along wth further dscusson of ths approach can be found n [6]. MODELING FRAMEWORK We begn by formulatng a model of the qualty of each ndvdual task as a functon of the tme and cost allocated to t. We assume that there could be dfferent enttes who could do the task and that each entty could do the job wth dfferent allocatons of tme and budget. Each entty would have ts own qualty functon n terms of tme and cost. If those qualty functons are graphed on the same tme/cost/qualty axes, then the overall qualty functon for the task that we are nterested n s the maxmum, or the upper envelope, of the ndvdual entty qualty graphs. We assume that ths overall qualty functon for a task has two basc propertes: Holdng tme constant, qualty s nondecreasng n cost. Thus f tme s fxed, we assume that spendng more money on the task wll ncrease (or at least not decrease) the qualty. Holdng cost constant, qualty s nondecreasng n tme. Thus f cost s fxed, we assume that spendng more tme on the task wll ncrease (or at least not decrease) the qualty. If we normalze qualty to be on a scale, and lmt tme and cost to reasonable values for the task at hand, based on the two nondecreasng assumptons above, we would expect the graph to show the qualty beng lowest at the corner of the doman wth the smallest values of tme and cost and hghest n the opposte corner (the hghest values of tme and cost). For a fxed qualty, we would expect a tradtonal tme/cost tradeoff curve, whch s normally a decreasng convex curve (to mantan the same level of qualty, to reduce the tme, one has to pay more money, such as n standard project actvty crashng [1]). Ths suggests a basc hll shape rsng out of a plan, although we would only be nterested n a onequarter wedge of the hll. A famlar mathematcal functonal form that has ths shape s the bvarate normal dstrbuton * n probablty. We propose usng ths functonal form for the overall qualty functon for each task. Our qualty functon s normalzed so that the maxmum tme ( µ t ) and cost ( µ c ) values consdered reasonably correspond to a qualty of 100. The standard devaton parameters ( σ t and σ c ) gve a measure of how slowly the qualty drops from the top of the hll compared to the maxmum values for tme and cost, respectvely. Thus, our resultng qualty functon s gven by * Ths verson of the bvarate normal dstrbuton assumes ndependence of the two random varables. We have chosen ths verson for a smpler model, but the dependent verson could also be used, wth one more parameter, correspondng to the correlaton between the varables.
3 Qtc (, ) = 100e t μ 2 2 t c μc ( σ ) ( σ ) + t c We have normalzed the ntal constant to 100 and elmnated the ½ n the exponent (whch means that each σ would be multpled by 2 to be nterpreted as the usual σ n the bvarate normal). If we hold ether varable constant, the margnal graph for the other wll be a bell curve (actually, a subset of a graph that s a constant multple of a normal dstrbuton curve). The upper envelope graph may not be smooth, but we are assumng that we can create a smooth functon that s a reasonable estmate of the upper envelope. In stuatons where n bds specfyng levels of qualty, tme, and cost ( qj, tj, c j) have been receved for a gven actvty, the four parameters of the bvarate normal functon can be determned usng nonlnear least squares estmaton. MODEL FORMULATION We start wth standard assumptons for modelng projects: that the project network has no cycles, that the start actvty (actvty 0, a dummy actvty) s the only actvty that s not an mmedate successor 1 of any actvty, and that the fnsh actvty (actvty N+1, also a dummy actvty) s the only actvty that has no successors..defne the followng parameters and varables: t = the duraton of actvty, for = 1,,N c = the cost of actvty, for = 1,,N q = the qualty of actvty, for = 1,,N S = the set of actvtes that are mmedate successors of actvty, for = 0,,N T UB = upper bound on the total project tme Q = lower bound on project qualty st = the scheduled start tme for actvty, for = 0,,N+1 t = lower bound on the duraton of actvty, for = 1,,N mn c mn = lower bound on the cost of actvty, for = 1,,N Relevant qualty measures could nvolve maxmzng average qualty, or maxmzng mnmum qualty, of the tasks. We select the latter, Q mn, as our qualty metrc, snce from a systems perspectve f the project s vewed as an ntegrated set of actvtes, the qualty of a project s only as hgh as ts weakest lnk. Q mn s defned as: mn q Q mn = (1) 1 N In our formulaton, we mnmze total project cost whle settng a lower bound on Q mn and an upper bound on total project tme. The nonlnear program s gven as equatons (2) (12): 1 It s common to use predecessors rather than successors for formulatons of ths type, but for ths example, the formulaton turns out to be much more concse and elegant usng successors.
4 Mnmze N c (2) = 1 Subject to: Qmn q, = 1,2,,... N (3) 2 2 { μt σt μt σt } Qt (, c) = 100 * exp [( t ) / )] [( c ) / )], = 1,2,,... N (4) Q mn 0 0 Q (5) st = (6) st st + t = 0,..., N, k S (7) st k N+ 1 T (8) UB st 0 = 1,..., N + 1 (9) tmn t, 1,2,..., μt = N (10) cmn c, 1,2,..., μc = N (11) q, t, c 0, = 1,2,..., N (12) Ths problem can be solved usng Lngo s global solver [4] and extends the standard cost tme tradeoff problem [1]. CONSTRUCTION EXAMPLE A general contractor plannng to start constructon of a new house has organzed the project nto actvtes as gven n Table 1. The correspondng project network dagram s shown n Fgure 1. She has receved bds for both duraton and cost from dfferent subcontractors. These bds were used to estmate the bvarate normal qualty functons for each actvty (Table 1). USING QUALITY LEVEL CURVE GRAPHS One way to evaluate the nteractve relaton among project tme, total cost, and qualty s to create level soqualty graphs. Specfyng a value of Q, for dfferent total project tmes (upper lmts), usng our model we can then fnd the mnmum cost possble that fnshes the project wthn a gven tme and mantans a mnmum qualty of at least Q. A set of level soqualty curves for the constructon example s shown n Fgure 2. The graph for a hgher qualty level les above and to the rght of that for a lower qualty level, although they can overlap n places for qualty levels that are very close together. There are several places where a level curve s horzontal. Ths could mean that to acheve a certan qualty level, a choce may need to be made at a longer project tme value that forces a soluton whch actually fnshes the project n strctly less than the upper lmt for the total tme, and therefore the same soluton s optmal at a shorter project tme lmt. Fgure 2 provdes a concse summary of the relatonshp among tme, cost, and qualty, and can be used to make wellnformed decsons about how to execute the project.
5 Table 1: Task, Immedate Successor, and Qualty Functon Informaton for Constructon Project IMMEDIATE TASK DESCRIPTION SUCCESSORS ( t, t, c, c) QUALITY PARAMETERS μ σ μ σ 0 START 1 dummy actvty 1 Excavate and Pour Footers 2 Not estmated one bd* 2 Pour Concrete Foundaton 3 Not estmated one bd* 3 Erect Rough Wall & Roof 4,5,6 (4, 1.79, 48.6, 42) 4 Install Sdng 11 (13, 19, 79.2, 99.4) 5 Install Plumbng 7 (3, 1.62, 26.6, 20.4) 6 Install Electrcal 7 (10.9, 12.8, 29.7, 77.9) 7 Install Wallboard 8,9 (5, 2.73, 16.8, 8.05) 8 Lay Floorng 10 (8.09, 7.18, 64, 67.5) 9 Do Interor Pantng 10 (4.57, 4.3, 16.8, 12.7) 10 Install Interor Fxtures 13 Not estmated one bd* 11 Install Gutters & Downspouts 12 (2, 12, 17.7, 18.9) 12 Do Gradng & Landscapng 13 (3.36, 2.4, 21.5, 12.3) 13 FINISH  dummy actvty *for those actvtes havng one bd, the qualty, tme, and cost (q, t, c) estmates were used drectly n the analyss: actvty 1: (70, 3, 26.6); actvty 2: (70, 1, 7.2); actvty 10: (70, 3, 7.2) Fgure 1: Project Network Dagram for Constructon Example CONCLUSIONS In standard project plannng and schedulng, qualty s acknowledged to be mportant at dfferent levels, but prevously has not been explctly modeled. In many stuatons there are alternate optons for accomplshng project actvtes, and these nvolve dfferng levels of tme, cost, and qualty. In such stuatons t makes sense to model the relatonshp between cost, tme, and qualty, and determne ther levels for each actvty that best acheves the project s objectves. We have presented a nonlnear programmng model for the qualty/tme/cost problem, and have shown how qualty level curves can be a very useful management tool n makng fnal project schedulng decsons that explctly model and ncorporate qualty.
6 Fgure 2: IsoQualty Curves for Constructon Example total project cost project completon tme REFERENCES [1] Brucker, P., Drexl, A., Mohrng, R., Neumann, K., Pesch, E. Resourceconstraned project schedulng: Notaton, classfcaton, models, and methods, European Journal of Operatonal Research, 1999, 112(1), [2] Goetsch, D. L., Davs, S. B. Qualty management (5 th ed.). Upper Saddle Rver, NJ: Pearson PrentceHall, [3] Internatonal Organzaton for Standards, ISO 9000:2000, [4] Lndo Systems. Lngo Verson 9.0. Chcago, [5] Paqun, J. P., Coullard, J., Ferrand, D. J. Assessng and controllng the qualty of a project end product: The earned qualty method, IEEE Transactons on Engneerng Management, 2000, 47(10), [6] PollackJohnson, B., Lberatore, M. Incorporatng Qualty Consderatons nto Project Tme/Cost Tradeoff Analyss and Decson Makng, IEEE Transactons on Engneerng Management, 2006, 53(4), [7] Project Management Insttute. A Gude to the project management body of knowledge 3 rd ed. Newtown Square, PA, [8] Saaty, T. L. A Scalng method for prortes n herarchcal structures, Journal of Mathematcal Psychology, 1977, 15, [9] Saaty, T. L. The analytc herarchy process. Pttsburgh: RWS Publcatons, 1996.
PowerofTwo Policies for Single Warehouse MultiRetailer Inventory Systems with Order Frequency Discounts
Powerofwo Polces for Sngle Warehouse MultRetaler Inventory Systems wth Order Frequency Dscounts José A. Ventura Pennsylvana State Unversty (USA) Yale. Herer echnon Israel Insttute of echnology (Israel)
More informationProject Networks With MixedTime Constraints
Project Networs Wth MxedTme Constrants L Caccetta and B Wattananon Western Australan Centre of Excellence n Industral Optmsaton (WACEIO) Curtn Unversty of Technology GPO Box U1987 Perth Western Australa
More informationCommunication Networks II Contents
8 / 1  Communcaton Networs II (Görg)  www.comnets.unbremen.de Communcaton Networs II Contents 1 Fundamentals of probablty theory 2 Traffc n communcaton networs 3 Stochastc & Marovan Processes (SP
More informationOn the Optimal Control of a Cascade of HydroElectric Power Stations
On the Optmal Control of a Cascade of HydroElectrc Power Statons M.C.M. Guedes a, A.F. Rbero a, G.V. Smrnov b and S. Vlela c a Department of Mathematcs, School of Scences, Unversty of Porto, Portugal;
More informationA DYNAMIC CRASHING METHOD FOR PROJECT MANAGEMENT USING SIMULATIONBASED OPTIMIZATION. Michael E. Kuhl Radhamés A. TolentinoPeña
Proceedngs of the 2008 Wnter Smulaton Conference S. J. Mason, R. R. Hll, L. Mönch, O. Rose, T. Jefferson, J. W. Fowler eds. A DYNAMIC CRASHING METHOD FOR PROJECT MANAGEMENT USING SIMULATIONBASED OPTIMIZATION
More informationAn Integrated Approach of AHPGP and Visualization for Software Architecture Optimization: A casestudy for selection of architecture style
Internatonal Journal of Scentfc & Engneerng Research Volume 2, Issue 7, July20 An Integrated Approach of AHPGP and Vsualzaton for Software Archtecture Optmzaton: A casestudy for selecton of archtecture
More informationAnswer: A). There is a flatter IS curve in the high MPC economy. Original LM LM after increase in M. IS curve for low MPC economy
4.02 Quz Solutons Fall 2004 MultpleChoce Questons (30/00 ponts) Please, crcle the correct answer for each of the followng 0 multplechoce questons. For each queston, only one of the answers s correct.
More informationPSYCHOLOGICAL RESEARCH (PYC 304C) Lecture 12
14 The Chsquared dstrbuton PSYCHOLOGICAL RESEARCH (PYC 304C) Lecture 1 If a normal varable X, havng mean µ and varance σ, s standardsed, the new varable Z has a mean 0 and varance 1. When ths standardsed
More informationActivity Scheduling for CostTime Investment Optimization in Project Management
PROJECT MANAGEMENT 4 th Internatonal Conference on Industral Engneerng and Industral Management XIV Congreso de Ingenería de Organzacón Donosta San Sebastán, September 8 th 10 th 010 Actvty Schedulng
More informationModule 2 LOSSLESS IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur
Module LOSSLESS IMAGE COMPRESSION SYSTEMS Lesson 3 Lossless Compresson: Huffman Codng Instructonal Objectves At the end of ths lesson, the students should be able to:. Defne and measure source entropy..
More informationThe OC Curve of Attribute Acceptance Plans
The OC Curve of Attrbute Acceptance Plans The Operatng Characterstc (OC) curve descrbes the probablty of acceptng a lot as a functon of the lot s qualty. Fgure 1 shows a typcal OC Curve. 10 8 6 4 1 3 4
More informationbenefit is 2, paid if the policyholder dies within the year, and probability of death within the year is ).
REVIEW OF RISK MANAGEMENT CONCEPTS LOSS DISTRIBUTIONS AND INSURANCE Loss and nsurance: When someone s subject to the rsk of ncurrng a fnancal loss, the loss s generally modeled usng a random varable or
More informationPerformance Analysis of Energy Consumption of Smartphone Running Mobile Hotspot Application
Internatonal Journal of mart Grd and lean Energy Performance Analyss of Energy onsumpton of martphone Runnng Moble Hotspot Applcaton Yun on hung a chool of Electronc Engneerng, oongsl Unversty, 511 angdodong,
More informationGENETIC ALGORITHM FOR PROJECT SCHEDULING AND RESOURCE ALLOCATION UNDER UNCERTAINTY
Int. J. Mech. Eng. & Rob. Res. 03 Fady Safwat et al., 03 Research Paper ISS 78 049 www.jmerr.com Vol., o. 3, July 03 03 IJMERR. All Rghts Reserved GEETIC ALGORITHM FOR PROJECT SCHEDULIG AD RESOURCE ALLOCATIO
More informationThe Development of Web Log Mining Based on ImproveKMeans Clustering Analysis
The Development of Web Log Mnng Based on ImproveKMeans Clusterng Analyss TngZhong Wang * College of Informaton Technology, Luoyang Normal Unversty, Luoyang, 471022, Chna wangtngzhong2@sna.cn Abstract.
More informationAllocating Time and Resources in Project Management Under Uncertainty
Proceedngs of the 36th Hawa Internatonal Conference on System Scences  23 Allocatng Tme and Resources n Project Management Under Uncertanty Mark A. Turnqust School of Cvl and Envronmental Eng. Cornell
More informationSelecting Best Employee of the Year Using Analytical Hierarchy Process
J. Basc. Appl. Sc. Res., 5(11)7276, 2015 2015, TextRoad Publcaton ISSN 20904304 Journal of Basc and Appled Scentfc Research www.textroad.com Selectng Best Employee of the Year Usng Analytcal Herarchy
More informationCredit Limit Optimization (CLO) for Credit Cards
Credt Lmt Optmzaton (CLO) for Credt Cards Vay S. Desa CSCC IX, Ednburgh September 8, 2005 Copyrght 2003, SAS Insttute Inc. All rghts reserved. SAS Propretary Agenda Background Tradtonal approaches to credt
More informationINVESTIGATION OF VEHICULAR USERS FAIRNESS IN CDMAHDR NETWORKS
21 22 September 2007, BULGARIA 119 Proceedngs of the Internatonal Conference on Informaton Technologes (InfoTech2007) 21 st 22 nd September 2007, Bulgara vol. 2 INVESTIGATION OF VEHICULAR USERS FAIRNESS
More informationDEFINING %COMPLETE IN MICROSOFT PROJECT
CelersSystems DEFINING %COMPLETE IN MICROSOFT PROJECT PREPARED BY James E Aksel, PMP, PMISP, MVP For Addtonal Informaton about Earned Value Management Systems and reportng, please contact: CelersSystems,
More information1 Approximation Algorithms
CME 305: Dscrete Mathematcs and Algorthms 1 Approxmaton Algorthms In lght of the apparent ntractablty of the problems we beleve not to le n P, t makes sense to pursue deas other than complete solutons
More informationCausal, Explanatory Forecasting. Analysis. Regression Analysis. Simple Linear Regression. Which is Independent? Forecasting
Causal, Explanatory Forecastng Assumes causeandeffect relatonshp between system nputs and ts output Forecastng wth Regresson Analyss Rchard S. Barr Inputs System Cause + Effect Relatonshp The job of
More informationAN APPOINTMENT ORDER OUTPATIENT SCHEDULING SYSTEM THAT IMPROVES OUTPATIENT EXPERIENCE
AN APPOINTMENT ORDER OUTPATIENT SCHEDULING SYSTEM THAT IMPROVES OUTPATIENT EXPERIENCE YuL Huang Industral Engneerng Department New Mexco State Unversty Las Cruces, New Mexco 88003, U.S.A. Abstract Patent
More informationAn MILP model for planning of batch plants operating in a campaignmode
An MILP model for plannng of batch plants operatng n a campagnmode Yanna Fumero Insttuto de Desarrollo y Dseño CONICET UTN yfumero@santafeconcet.gov.ar Gabrela Corsano Insttuto de Desarrollo y Dseño
More informationHow Sets of Coherent Probabilities May Serve as Models for Degrees of Incoherence
1 st Internatonal Symposum on Imprecse Probabltes and Ther Applcatons, Ghent, Belgum, 29 June 2 July 1999 How Sets of Coherent Probabltes May Serve as Models for Degrees of Incoherence Mar J. Schervsh
More informationAn Alternative Way to Measure Private Equity Performance
An Alternatve Way to Measure Prvate Equty Performance Peter Todd Parlux Investment Technology LLC Summary Internal Rate of Return (IRR) s probably the most common way to measure the performance of prvate
More informationFeature selection for intrusion detection. Slobodan Petrović NISlab, Gjøvik University College
Feature selecton for ntruson detecton Slobodan Petrovć NISlab, Gjøvk Unversty College Contents The feature selecton problem Intruson detecton Traffc features relevant for IDS The CFS measure The mrmr measure
More informationA Novel Methodology of Working Capital Management for Large. Public Constructions by Using Fuzzy Scurve Regression
Novel Methodology of Workng Captal Management for Large Publc Constructons by Usng Fuzzy Scurve Regresson ChengWu Chen, Morrs H. L. Wang and TngYa Hseh Department of Cvl Engneerng, Natonal Central Unversty,
More informationFixed income risk attribution
5 Fxed ncome rsk attrbuton Chthra Krshnamurth RskMetrcs Group chthra.krshnamurth@rskmetrcs.com We compare the rsk of the actve portfolo wth that of the benchmark and segment the dfference between the two
More informationOptimal Bidding Strategies for Generation Companies in a DayAhead Electricity Market with Risk Management Taken into Account
Amercan J. of Engneerng and Appled Scences (): 86, 009 ISSN 94700 009 Scence Publcatons Optmal Bddng Strateges for Generaton Companes n a DayAhead Electrcty Market wth Rsk Management Taken nto Account
More informationLuby s Alg. for Maximal Independent Sets using Pairwise Independence
Lecture Notes for Randomzed Algorthms Luby s Alg. for Maxmal Independent Sets usng Parwse Independence Last Updated by Erc Vgoda on February, 006 8. Maxmal Independent Sets For a graph G = (V, E), an ndependent
More informationDetermination of Integrated Risk Degrees in Product Development Project
Proceedngs of the World Congress on Engneerng and Computer Scence 009 Vol II WCECS 009, October 0, 009, San Francsco, USA Determnaton of Integrated sk Degrees n Product Development Project D. W. Cho.,
More informationBUSINESS PROCESS PERFORMANCE MANAGEMENT USING BAYESIAN BELIEF NETWORK. 0688, dskim@ssu.ac.kr
Proceedngs of the 41st Internatonal Conference on Computers & Industral Engneerng BUSINESS PROCESS PERFORMANCE MANAGEMENT USING BAYESIAN BELIEF NETWORK Yeongbn Mn 1, Yongwoo Shn 2, Km Jeehong 1, Dongsoo
More informationLIFETIME INCOME OPTIONS
LIFETIME INCOME OPTIONS May 2011 by: Marca S. Wagner, Esq. The Wagner Law Group A Professonal Corporaton 99 Summer Street, 13 th Floor Boston, MA 02110 Tel: (617) 3575200 Fax: (617) 3575250 www.ersalawyers.com
More informationA Novel Auction Mechanism for Selling TimeSensitive EServices
A ovel Aucton Mechansm for Sellng TmeSenstve EServces JuongSk Lee and Boleslaw K. Szymansk Optmaret Inc. and Department of Computer Scence Rensselaer Polytechnc Insttute 110 8 th Street, Troy, Y 12180,
More informationResearch Article Enhanced TwoStep Method via Relaxed Order of αsatisfactory Degrees for Fuzzy Multiobjective Optimization
Hndaw Publshng Corporaton Mathematcal Problems n Engneerng Artcle ID 867836 pages http://dxdoorg/055/204/867836 Research Artcle Enhanced TwoStep Method va Relaxed Order of αsatsfactory Degrees for Fuzzy
More informationEffective Network Defense Strategies against Malicious Attacks with Various Defense Mechanisms under Quality of Service Constraints
Effectve Network Defense Strateges aganst Malcous Attacks wth Varous Defense Mechansms under Qualty of Servce Constrants Frank YeongSung Ln Department of Informaton Natonal Tawan Unversty Tape, Tawan,
More informationEnabling P2P Oneview Multiparty Video Conferencing
Enablng P2P Onevew Multparty Vdeo Conferencng Yongxang Zhao, Yong Lu, Changja Chen, and JanYn Zhang Abstract MultParty Vdeo Conferencng (MPVC) facltates realtme group nteracton between users. Whle P2P
More informationSurvey on Virtual Machine Placement Techniques in Cloud Computing Environment
Survey on Vrtual Machne Placement Technques n Cloud Computng Envronment Rajeev Kumar Gupta and R. K. Paterya Department of Computer Scence & Engneerng, MANIT, Bhopal, Inda ABSTRACT In tradtonal data center
More informationStudy on CET4 Marks in China s Graded English Teaching
Study on CET4 Marks n Chna s Graded Englsh Teachng CHE We College of Foregn Studes, Shandong Insttute of Busness and Technology, P.R.Chna, 264005 Abstract: Ths paper deploys Logt model, and decomposes
More informationMAC Layer Service Time Distribution of a Fixed Priority Real Time Scheduler over 802.11
Internatonal Journal of Software Engneerng and Its Applcatons Vol., No., Aprl, 008 MAC Layer Servce Tme Dstrbuton of a Fxed Prorty Real Tme Scheduler over 80. Inès El Korb Ecole Natonale des Scences de
More informationEfficient Project Portfolio as a tool for Enterprise Risk Management
Effcent Proect Portfolo as a tool for Enterprse Rsk Management Valentn O. Nkonov Ural State Techncal Unversty Growth Traectory Consultng Company January 5, 27 Effcent Proect Portfolo as a tool for Enterprse
More informationMultiplePeriod Attribution: Residuals and Compounding
MultplePerod Attrbuton: Resduals and Compoundng Our revewer gave these authors full marks for dealng wth an ssue that performance measurers and vendors often regard as propretary nformaton. In 1994, Dens
More informationResource Allocation: Marketing Engineering Technical Note 1
Resource Allocaton: Marketng Engneerng Techncal Note 1 Table of contents Introducton Response Functons Specfcaton and Calbraton Optmzng Resource Deployment Call Plannng for a Salesperson Resource Plannng
More informationThe Greedy Method. Introduction. 0/1 Knapsack Problem
The Greedy Method Introducton We have completed data structures. We now are gong to look at algorthm desgn methods. Often we are lookng at optmzaton problems whose performance s exponental. For an optmzaton
More informationData Broadcast on a MultiSystem Heterogeneous Overlayed Wireless Network *
JOURNAL OF INFORMATION SCIENCE AND ENGINEERING 24, 819840 (2008) Data Broadcast on a MultSystem Heterogeneous Overlayed Wreless Network * Department of Computer Scence Natonal Chao Tung Unversty Hsnchu,
More informationJ. Parallel Distrib. Comput.
J. Parallel Dstrb. Comput. 71 (2011) 62 76 Contents lsts avalable at ScenceDrect J. Parallel Dstrb. Comput. journal homepage: www.elsever.com/locate/jpdc Optmzng server placement n dstrbuted systems n
More informationA Lyapunov Optimization Approach to Repeated Stochastic Games
PROC. ALLERTON CONFERENCE ON COMMUNICATION, CONTROL, AND COMPUTING, OCT. 2013 1 A Lyapunov Optmzaton Approach to Repeated Stochastc Games Mchael J. Neely Unversty of Southern Calforna http://wwwbcf.usc.edu/
More informationx f(x) 1 0.25 1 0.75 x 1 0 1 1 0.04 0.01 0.20 1 0.12 0.03 0.60
BIVARIATE DISTRIBUTIONS Let be a varable that assumes the values { 1,,..., n }. Then, a functon that epresses the relatve frequenc of these values s called a unvarate frequenc functon. It must be true
More information2.4 Bivariate distributions
page 28 2.4 Bvarate dstrbutons 2.4.1 Defntons Let X and Y be dscrete r.v.s defned on the same probablty space (S, F, P). Instead of treatng them separately, t s often necessary to thnk of them actng together
More informationA Secure PasswordAuthenticated Key Agreement Using Smart Cards
A Secure PasswordAuthentcated Key Agreement Usng Smart Cards Ka Chan 1, WenChung Kuo 2 and JnChou Cheng 3 1 Department of Computer and Informaton Scence, R.O.C. Mltary Academy, Kaohsung 83059, Tawan,
More informationLittle s Law & Bottleneck Law
Lttle s Law & Bottleneck Law Dec 20 I professonals have shunned performance modellng consderng t to be too complex and napplcable to real lfe. A lot has to do wth fear of mathematcs as well. hs tutoral
More informationFault tolerance in cloud technologies presented as a service
Internatonal Scentfc Conference Computer Scence 2015 Pavel Dzhunev, PhD student Fault tolerance n cloud technologes presented as a servce INTRODUCTION Improvements n technques for vrtualzaton and performance
More informationInequality and The Accounting Period. Quentin Wodon and Shlomo Yitzhaki. World Bank and Hebrew University. September 2001.
Inequalty and The Accountng Perod Quentn Wodon and Shlomo Ytzha World Ban and Hebrew Unversty September Abstract Income nequalty typcally declnes wth the length of tme taen nto account for measurement.
More information1.1 The University may award Higher Doctorate degrees as specified from timetotime in UPR AS11 1.
HIGHER DOCTORATE DEGREES SUMMARY OF PRINCIPAL CHANGES General changes None Secton 3.2 Refer to text (Amendments to verson 03.0, UPR AS02 are shown n talcs.) 1 INTRODUCTION 1.1 The Unversty may award Hgher
More informationFORCED CONVECTION HEAT TRANSFER IN A DOUBLE PIPE HEAT EXCHANGER
FORCED CONVECION HEA RANSFER IN A DOUBLE PIPE HEA EXCHANGER Dr. J. Mchael Doster Department of Nuclear Engneerng Box 7909 North Carolna State Unversty Ralegh, NC 276957909 Introducton he convectve heat
More informationIMPACT ANALYSIS OF A CELLULAR PHONE
4 th ASA & μeta Internatonal Conference IMPACT AALYSIS OF A CELLULAR PHOE We Lu, 2 Hongy L Bejng FEAonlne Engneerng Co.,Ltd. Bejng, Chna ABSTRACT Drop test smulaton plays an mportant role n nvestgatng
More informationMultiPeriod Resource Allocation for Estimating Project Costs in Competitive Bidding
Department of Industral Engneerng and Management Techncall Report No. 20146 MultPerod Resource Allocaton for Estmatng Project Costs n Compettve dng Yuch Takano, Nobuak Ish, and Masaak Murak September,
More informationMarginal Returns to Education For Teachers
The Onlne Journal of New Horzons n Educaton Volume 4, Issue 3 MargnalReturnstoEducatonForTeachers RamleeIsmal,MarnahAwang ABSTRACT FacultyofManagementand Economcs UnverstPenddkanSultan Idrs ramlee@fpe.ups.edu.my
More informationLei Liu, Hua Yang Business School, Hunan University, Changsha, Hunan, P.R. China, 410082. Abstract
, pp.377390 http://dx.do.org/10.14257/jsa.2016.10.4.34 Research on the Enterprse Performance Management Informaton System Development and Robustness Optmzaton based on Data Regresson Analyss and Mathematcal
More informationChapter 4 ECONOMIC DISPATCH AND UNIT COMMITMENT
Chapter 4 ECOOMIC DISATCH AD UIT COMMITMET ITRODUCTIO A power system has several power plants. Each power plant has several generatng unts. At any pont of tme, the total load n the system s met by the
More informationRate Monotonic (RM) Disadvantages of cyclic. TDDB47 Real Time Systems. Lecture 2: RM & EDF. Prioritybased scheduling. States of a process
Dsadvantages of cyclc TDDB47 Real Tme Systems Manual scheduler constructon Cannot deal wth any runtme changes What happens f we add a task to the set? RealTme Systems Laboratory Department of Computer
More informationThe Application of Fractional Brownian Motion in Option Pricing
Vol. 0, No. (05), pp. 738 http://dx.do.org/0.457/jmue.05.0..6 The Applcaton of Fractonal Brownan Moton n Opton Prcng Qngxn Zhou School of Basc Scence,arbn Unversty of Commerce,arbn zhouqngxn98@6.com
More informationResearch of Network System Reconfigurable Model Based on the Finite State Automation
JOURNAL OF NETWORKS, VOL., NO. 5, MAY 24 237 Research of Network System Reconfgurable Model Based on the Fnte State Automaton Shenghan Zhou and Wenbng Chang School of Relablty and System Engneerng, Behang
More informationSoftware project management with GAs
Informaton Scences 177 (27) 238 241 www.elsever.com/locate/ns Software project management wth GAs Enrque Alba *, J. Francsco Chcano Unversty of Málaga, Grupo GISUM, Departamento de Lenguajes y Cencas de
More informationL10: Linear discriminants analysis
L0: Lnear dscrmnants analyss Lnear dscrmnant analyss, two classes Lnear dscrmnant analyss, C classes LDA vs. PCA Lmtatons of LDA Varants of LDA Other dmensonalty reducton methods CSCE 666 Pattern Analyss
More informationApplication of MultiAgents for Fault Detection and Reconfiguration of Power Distribution Systems
1 Applcaton of MultAgents for Fault Detecton and Reconfguraton of Power Dstrbuton Systems K. Nareshkumar, Member, IEEE, M. A. Choudhry, Senor Member, IEEE, J. La, A. Felach, Senor Member, IEEE AbstractThe
More informationThe covariance is the two variable analog to the variance. The formula for the covariance between two variables is
Regresson Lectures So far we have talked only about statstcs that descrbe one varable. What we are gong to be dscussng for much of the remander of the course s relatonshps between two or more varables.
More informationComplex Service Provisioning in Collaborative Cloud Markets
Melane Sebenhaar, Ulrch Lampe, Tm Lehrg, Sebastan Zöller, Stefan Schulte, Ralf Stenmetz: Complex Servce Provsonng n Collaboratve Cloud Markets. In: W. Abramowcz et al. (Eds.): Proceedngs of the 4th European
More informationOutsourcing inventory management decisions in healthcare: Models and application
European Journal of Operatonal Research 154 (24) 271 29 O.R. Applcatons Outsourcng nventory management decsons n healthcare: Models and applcaton www.elsever.com/locate/dsw Lawrence Ncholson a, Asoo J.
More informationOn the Interaction between Load Balancing and Speed Scaling
On the Interacton between Load Balancng and Speed Scalng Ljun Chen, Na L and Steven H. Low Engneerng & Appled Scence Dvson, Calforna Insttute of Technology, USA Abstract Speed scalng has been wdely adopted
More informationThe Analysis of Outliers in Statistical Data
THALES Project No. xxxx The Analyss of Outlers n Statstcal Data Research Team Chrysses Caron, Assocate Professor (P.I.) Vaslk Karot, Doctoral canddate Polychrons Economou, Chrstna Perrakou, Postgraduate
More informationCalculation of Sampling Weights
Perre Foy Statstcs Canada 4 Calculaton of Samplng Weghts 4.1 OVERVIEW The basc sample desgn used n TIMSS Populatons 1 and 2 was a twostage stratfed cluster desgn. 1 The frst stage conssted of a sample
More informationFINANCIAL MATHEMATICS. A Practical Guide for Actuaries. and other Business Professionals
FINANCIAL MATHEMATICS A Practcal Gude for Actuares and other Busness Professonals Second Edton CHRIS RUCKMAN, FSA, MAAA JOE FRANCIS, FSA, MAAA, CFA Study Notes Prepared by Kevn Shand, FSA, FCIA Assstant
More information2. SYSTEM MODEL. the SLA (unlike the only other related mechanism [15] we can compare it is never able to meet the SLA).
Managng Server Energy and Operatonal Costs n Hostng Centers Yyu Chen Dept. of IE Penn State Unversty Unversty Park, PA 16802 yzc107@psu.edu Anand Svasubramanam Dept. of CSE Penn State Unversty Unversty
More informationOn the Interaction between Load Balancing and Speed Scaling
On the Interacton between Load Balancng and Speed Scalng Ljun Chen and Na L Abstract Speed scalng has been wdely adopted n computer and communcaton systems, n partcular, to reduce energy consumpton. An
More informationTHE DISTRIBUTION OF LOAN PORTFOLIO VALUE * Oldrich Alfons Vasicek
HE DISRIBUION OF LOAN PORFOLIO VALUE * Oldrch Alfons Vascek he amount of captal necessary to support a portfolo of debt securtes depends on the probablty dstrbuton of the portfolo loss. Consder a portfolo
More informationTo manage leave, meeting institutional requirements and treating individual staff members fairly and consistently.
Corporate Polces & Procedures Human Resources  Document CPP216 Leave Management Frst Produced: Current Verson: Past Revsons: Revew Cycle: Apples From: 09/09/09 26/10/12 09/09/09 3 years Immedately Authorsaton:
More informationAbstract # 0150399 Working Capital Exposure: A Methodology to Control Economic Performance in Production Environment Projects
Abstract # 0150399 Workng Captal Exposure: A Methodology to Control Economc Performance n Producton Envronment Projects Dego F. Manotas. School of Industral Engneerng and Statstcs, Unversdad del Valle.
More information"Research Note" APPLICATION OF CHARGE SIMULATION METHOD TO ELECTRIC FIELD CALCULATION IN THE POWER CABLES *
Iranan Journal of Scence & Technology, Transacton B, Engneerng, ol. 30, No. B6, 789794 rnted n The Islamc Republc of Iran, 006 Shraz Unversty "Research Note" ALICATION OF CHARGE SIMULATION METHOD TO ELECTRIC
More information7.5. Present Value of an Annuity. Investigate
7.5 Present Value of an Annuty Owen and Anna are approachng retrement and are puttng ther fnances n order. They have worked hard and nvested ther earnngs so that they now have a large amount of money on
More informationStudy on Model of Risks Assessment of Standard Operation in Rural Power Network
Study on Model of Rsks Assessment of Standard Operaton n Rural Power Network Qngj L 1, Tao Yang 2 1 Qngj L, College of Informaton and Electrcal Engneerng, Shenyang Agrculture Unversty, Shenyang 110866,
More informationNumber of Levels Cumulative Annual operating Income per year construction costs costs ($) ($) ($) 1 600,000 35,000 100,000 2 2,200,000 60,000 350,000
Problem Set 5 Solutons 1 MIT s consderng buldng a new car park near Kendall Square. o unversty funds are avalable (overhead rates are under pressure and the new faclty would have to pay for tself from
More informationSingularity functions as new tool for integrated project management
Creatve Constructon Conference 24 Sngularty functons as new tool for ntegrated project management Gunnar LUCKO and Y SU Department of Cvl Engneerng, Catholc Unversty of Amerca, 62 Mchgan Avenue NE, Washngton,
More informationNONLINEAR OPTIMIZATION FOR PROJECT SCHEDULING AND RESOURCE ALLOCATION UNDER UNCERTAINTY
NONLINEAR OPTIMIZATION FOR PROJECT SCHEDULING AND RESOURCE ALLOCATION UNDER UNCERTAINTY A Dssertaton Presented to the Faculty of the Graduate School of Cornell Unversty In Partal Fulfllment of the Requrements
More informationA DATA MINING APPLICATION IN A STUDENT DATABASE
JOURNAL OF AERONAUTICS AND SPACE TECHNOLOGIES JULY 005 VOLUME NUMBER (5357) A DATA MINING APPLICATION IN A STUDENT DATABASE Şenol Zafer ERDOĞAN Maltepe Ünversty Faculty of Engneerng BüyükbakkalköyIstanbul
More informationMany etailers providing attended home delivery, especially egrocers, offer narrow delivery time slots to
Vol. 45, No. 3, August 2011, pp. 435 449 ssn 00411655 essn 15265447 11 4503 0435 do 10.1287/trsc.1100.0346 2011 INFORMS Tme Slot Management n Attended Home Delvery Nels Agatz Department of Decson and
More informationTraffic State Estimation in the Traffic Management Center of Berlin
Traffc State Estmaton n the Traffc Management Center of Berln Authors: Peter Vortsch, PTV AG, Stumpfstrasse, D763 Karlsruhe, Germany phone ++49/72/965/35, emal peter.vortsch@ptv.de Peter Möhl, PTV AG,
More informationAPPLICATION OF COMPUTER PROGRAMMING IN OPTIMIZATION OF TECHNOLOGICAL OBJECTIVES OF COLD ROLLING
Journal Journal of Chemcal of Chemcal Technology and and Metallurgy, 50, 6, 50, 2015, 6, 2015 638643 APPLICATION OF COMPUTER PROGRAMMING IN OPTIMIZATION OF TECHNOLOGICAL OBJECTIVES OF COLD ROLLING Abdrakhman
More informationRiskbased Fatigue Estimate of Deep Water Risers  Course Project for EM388F: Fracture Mechanics, Spring 2008
Rskbased Fatgue Estmate of Deep Water Rsers  Course Project for EM388F: Fracture Mechancs, Sprng 2008 Chen Sh Department of Cvl, Archtectural, and Envronmental Engneerng The Unversty of Texas at Austn
More informationSample Design in TIMSS and PIRLS
Sample Desgn n TIMSS and PIRLS Introducton Marc Joncas Perre Foy TIMSS and PIRLS are desgned to provde vald and relable measurement of trends n student achevement n countres around the world, whle keepng
More informationSupport Vector Machines
Support Vector Machnes Max Wellng Department of Computer Scence Unversty of Toronto 10 Kng s College Road Toronto, M5S 3G5 Canada wellng@cs.toronto.edu Abstract Ths s a note to explan support vector machnes.
More informationRisk Model of LongTerm Production Scheduling in Open Pit Gold Mining
Rsk Model of LongTerm Producton Schedulng n Open Pt Gold Mnng R Halatchev 1 and P Lever 2 ABSTRACT Open pt gold mnng s an mportant sector of the Australan mnng ndustry. It uses large amounts of nvestments,
More informationTHE METHOD OF LEAST SQUARES THE METHOD OF LEAST SQUARES
The goal: to measure (determne) an unknown quantty x (the value of a RV X) Realsaton: n results: y 1, y 2,..., y j,..., y n, (the measured values of Y 1, Y 2,..., Y j,..., Y n ) every result s encumbered
More informationORDER ALLOCATION FOR SERVICE SUPPLY CHAIN BASE ON THE CUSTOMER BEST DELIVERY TIME UNDER THE BACKGROUND OF BIG DATA
Internatonal Journal of Computer Scence and Applcatons, Technomathematcs Research Foundaton Vol. 13, No. 1, pp. 84 92, 2016 ORDER ALLOCATION FOR SERVICE SUPPLY CHAIN BASE ON THE CUSTOMER BEST DELIVERY
More informationAN APPROACH TO WIRELESS SCHEDULING CONSIDERING REVENUE AND USERS SATISFACTION
The Medterranean Journal of Computers and Networks, Vol. 2, No. 1, 2006 57 AN APPROACH TO WIRELESS SCHEDULING CONSIDERING REVENUE AND USERS SATISFACTION L. Bada 1,*, M. Zorz 2 1 Department of Engneerng,
More informationUSING GOAL PROGRAMMING TO INCREASE THE EFFICIENCY OF MARKETING CAMPAIGNS
Journal of Internatonal & Interdscplnary Busness Research Volume 2 Journal of Internatonal & Interdscplnary Busness Research Artcle 6 112015 USING GOAL PROGRAMMING TO INCREASE THE EFFICIENCY OF MARKETING
More informationReturn decomposing of absoluteperformance multiasset class portfolios. Working Paper  Nummer: 16
Return decomposng of absoluteperformance multasset class portfolos Workng Paper  Nummer: 16 2007 by Dr. Stefan J. Illmer und Wolfgang Marty; n: Fnancal Markets and Portfolo Management; March 2007; Volume
More informationProblem Set 3. a) We are asked how people will react, if the interest rate i on bonds is negative.
Queston roblem Set 3 a) We are asked how people wll react, f the nterest rate on bonds s negatve. When
More informationA hybrid global optimization algorithm based on parallel chaos optimization and outlook algorithm
Avalable onlne www.ocpr.com Journal of Chemcal and Pharmaceutcal Research, 2014, 6(7):18841889 Research Artcle ISSN : 09757384 CODEN(USA) : JCPRC5 A hybrd global optmzaton algorthm based on parallel
More information