《系统工程》课程教学资源（英文文献）Area Logistics System Based on System

AreaLogisticsSystemBasedonSystemDynamics ModelGUIShouping（桂寿平）,ZHUQiang（朱强）,LULifang（陆丽芳）College of Tra ffic and Communications, South China University of Technology, Gua ngzhou510640,ChinaAbstract: At present, there are few effective ways to analyze area logistics systems. This paper usessystem dynamics to analyze the area logistics system and establishes a systemdynamics model for thearea logistics system based on the characteristics of the area logistics system and system dynamicsNumerical simulations with the system dynamic model were used to analyze a logistic system.Analysis of the Guangzhou economy shows that the model can reflect the actual state ofthe systemobjectively and can be used to make policyand harmonize environment.Key words: system dynamics; area logistics system; simulationIntroductionWithChina's entry into WTO, modern logistics systems are indispensable for fast economic growthand increased market opening.Rational area logistics systems are needed to realize efficient logisticsin China. So, theoretical research that can effectively construct area logistic rationalization becomesmoreimportant.However,thereislittleeffectiveresearchonarealogisticsproblemswithfewresearchmethodsavailableLarge complicated systems, such as social and economic systems, can be more effectively analyzedusing the system dynamics method. The system dynamics model should include nonlinear dynamicmodels with multiple feedback and long-time delays in terms of consequence of social systems andobvious structure ofwhite box" Moreover, the motion of the dynamic systems is solved in computersimulations to analyze the effect ofdecision-making on the system motion. The key part ofthe systemdynamics model is not the data but the model design. The advantage of system dynamics models isthat they include decision trees with consequence and structure, which is the reason why othermethods (ie., econometrics, operational research and analysis of input and output) are not as effectiveas the system dynamics model in analyzing social and economic systems [1-5]This paper describes an area logistics model by us ing qualitative and quantitative system dynamics

Area Logistics System Based on System Dynamics Model GUI Shouping (桂寿平), ZHU Qiang (朱 强), LU Lifang (陆丽芳) College of Traffic and Communications, South China University of Technology, Guangzhou 510640, China Abstract: At present, there are few effective ways to analyze area logistics systems. This paper uses system dynamics to analyze the area logistics system and establishes a system dynamics model for the area logistics system based on the characteristics of the area logistics system and system dynamics. Numerical simulations with the system dynamic model were used to analyze a logistic system. Analysis of the Guangzhou economy shows that the model can reflect the actual state of the system objectively and can be used to make policy and harmonize environment. Key words: system dynamics; area logistics system; simulation Introduction With China’s entry into WTO, modern logistics systems are indispensable for fast economic growth and increased market opening. Rational area logistics systems are needed to realize efficient logistics in China. So, theoretical research that can effectively construct area logistic rationalization becomes more important. However, there is little effective research on area logistics problems with few research methods available. Large complicated systems, such as social and economic systems, can be more effectively analyzed using the system dynamics method. The system dynamics model should include nonlinear dynamic models with multiple feedback and long-time delays in terms of consequence of social systems and obvious structure of “white box”. Moreover, the motion of the dynamic systems is solved in computer simulations to analyze the effect of decision-making on the system motion. The key part of the system dynamics model is not the data but the model design. The advantage of system dynamics models is that they include decision trees with consequence and structure, which is the reason why other methods (i.e., econometrics, operational research and analysis of input and output) are not as effective as the system dynamics model in analyzing social and economic systems [1-5] . This paper describes an area logistics model by using qualitative and quantitative system dynamics

analyses. The information gathered was used to analyze the structure and behavior ofsystems toprovide a scientific basis for decision-making1SystemDynamicsModelforArea LogisticsSystemThe flow chart for the system dynamics model of the area logistics system is given in Fig. 1.The system flow chart illustrates the key steps in the system dynamics model:1)Specify goals and limits: including system boundaries, the system dynamics model researchobject, forecasting ofthe expected system state, observing system features, identifying problems andsystem states related to the problems, limiting the ranges of problems, and choosing appropriatesystem variables [6]2)Analyze the consequences ofsystem decisions: describing factors related to problems,explaining the inside relations among factors, creating a consequence chart, and separating andanalyzing feedback loops and their effects.3)Specify the level and rate variables in the feedback loops and their designs4)Establish the system dynamics model with the DYNAMO equation5)Use computer simulation for solving the DYNAMO equation with the original data and therelated variables to simulate different schemes. The results lead to result graphs and conclusionswhich are used to modify the procedures (equations) and the variables.6)Analyze the results to identify structural errors and the causes ofthese errors. The model maythen be modified with additional simulations until a satisfactory result is achieved

analyses. The information gathered was used to analyze the structure and behavior of systems to provide a scientific basis for decision-making. 1 System Dynamics Model for Area Logistics System The flow chart for the system dynamics model of the area logistics system is given in Fig. 1. The system flow chart illustrates the key steps in the system dynamics model: 1) Specify goals and limits: including system boundaries, the system dynamics model research object, forecasting of the expected system state, observing system features, identifying problems and system states related to the problems, limiting the ranges of problems, and choosing appropriate system variables [6] . 2) Analyze the consequences of system decisions: describing factors related to problems, explaining the inside relations among factors, creating a consequence chart, and separating and analyzing feedback loops and their effects. 3) Specify the level and rate variables in the feedback loops and their designs. 4) Establish the system dynamics model with the DYNAMO equation. 5) Use computer simulation for solving the DYNAMO equation with the original data and the related variables to simulate different schemes. The results lead to result graphs and conclusions which are used to modify the procedures (equations) and the variables. 6) Analyze the results to identify structural errors and the causes of these errors. The model may then be modified with additional simulations until a satisfactory result is achieved

Specify system controlmodel target1Analyze causalityEstablishsystemdynamicmodel flow chartSpecifycontradictoryrelationoffeedbackloopvariableSpecify all variables andparameterdimensions-Specify levels,rates.Specify initial valuesaffiliations,andconstantsand variable step sizesSpecify type of functionsEstimate the sizes ofNboth sides offunctionsTYCompile theDYNAMOfunctionsComputer simulation1Analyze the resultsFig.1 Systemdynamics flowdiagram2 MathematicalModel forArea Logistics SystemThe basic relations between the different parts of the system are given in the consequence chart inFig. 2, which gives an initial layout of the system designInFig.2,the arrows indicate consequence links between twofactors.The plus and minus signsindicate how the two factors influence each other.The plus indicates that the variable at the arrowtipwill increase as the variable at the arrow base increases[7,8], The minus indicates adverse relations

Fig.1 System dynamics flow diagram 2 Mathematical Model for Area Logistics System The basic relations between the different parts of the system are given in the consequence chart in Fig. 2, which gives an initial layout of the system design In Fig. 2, the arrows indicate consequence links between two factors. The plus and minus signs indicate how the two factors influence each other. The plus indicates that the variable at the arrow tip will increase as the variable at the arrow base increases[7,8] . The minus indicates adverse relations

BFGCGPDABRINGREILCLD4cALC++XBRLDGRLDLR+.DCIFLC+LCCFSGC+DLAGRLA1+++LCRIIFIIE/RIDCL+betweenvariablesFig.2 Cause and effect in an area logistics systemThe consequence chart only describes the basic feedback structure framework, not the differencesbetween the different variables. The system consequence chart can be used to develop the systemdynamicsmodelforthearealogisticssystemshowninFig.3There are 29 variables in this model Among these variables, three are level variables, four are ratevariable, seventeen are descriptive variables, two are constants, and three are self-defined variables.Variable definitions:GDP:gross domestic product, NGRE: natural economic growth rate; BRL: logistics baffle rate;GCGP: gross product growth coefficient; BF: baffle factors; ILC: ideal logistics cost; IC: idealcoefficient;LD:

between variables. Fig. 2 Cause and effect in an area logistics system The consequence chart only describes the basic feedback structure framework, not the differences between the different variables. The system consequence chart can be used to develop the system dynamics model for the area logistics system shown in Fig.3. There are 29 variables in this model. Among these variables, three are level variables, four are rate variable, seventeen are descriptive variables, two are constants, and three are self-defined variables. Variable definitions: GDP: gross domestic product; NGRE: natural economic growth rate; BRL: logistics baffle rate; GCGP: gross product growth coefficient; BF: baffle factors; ILC: ideal logistics cost; IC: ideal coefficient; LD:

GCGFBFGDPNGREBRLICTimeDDILCLDALCDCLRGRLDBRLDIFLC<Time<Time>CFSGC.LADLAGRLARIE)DCIIFRIFig. 3 System dynamics model for an area logistics systemlogistics difference; ALC: actual logistics cost; LR: logistics requirement; GRLD: logistics demandgrowthrate; BRLD: logistics demand bafflerate;DC:demand coefficient, LC:logistics cost; IFLC:logistics cost influence factor; CF: cost factor, LA: logistics ability; GRLA: logistic ability growthrate; DLA: logistic ability dissipative rate;IE: investment effect, LI: logistics investment, IFI:investmentinfluencefactor;DCL:logisticsdissipativecoefficient,IED:investmenteffectdelay,CRIinvestment convers ion rate; RI: investment ratio; DD: difference delay; SGC: self growth coeffic ient.The systemequations are (DYNAMO equations run on Vensim_ple32):GDP=INTEG (NGRE - BRL);NGRE= GDPxGCGP;BRL=NGRExBFC (DD/ILC);LD=ALC-ILC:DD=DELAY3 (LD, delay time);ILC=LDxthe chart ofIC;LD = INTEG (GRLD- BRLD);GRLD= GDPxthe form ofDC (LA/ LD);BRLD=GRLDxinfluential factorschartofLC:LA= INTEG (GRLA- DRLA);GRLA=LAxSGC+thedelayofIExCRI

Fig. 3 System dynamics model for an area logistics system logistics difference; ALC: actual logistics cost; LR: logistics requirement; GRLD: logistics demand growthrate; BRLD: logistics demand baffle rate; DC: demand coefficient; LC: logistics cost; IFLC: logistics cost influence factor; CF: cost factor; LA: logistics ability; GRLA: logistic ability growth rate; DLA: logistic ability dissipative rate; IE: investment effect; LI: logistics investment; IFI: investment influence factor; DCL: logistics dissipative coefficient; IED: investment effect delay; CRI: investment conversion rate; RI: investment ratio; DD: difference delay; SGC: self growth coefficient. The system equations are (DYNAMO equations run on Vensim_ple32): GDP=INTEG (NGRE – BRL); NGRE = GDP×GCGP; BRL = NGRE×BFC (DD/ILC); LD=ALC – ILC; DD=DELAY3 (LD, delay time); ILC=LD×the chart of IC; LD = INTEG (GRLD – BRLD); GRLD = GDP×the form of DC (LA / LD); BRLD = GRLD×influential factors chart of LC; LA = INTEG (GRLA – DRLA); GRLA = LA×SGC + the delay of IE×CRI;