外文翻譯--基于系統(tǒng)動力學(xué)模型的區(qū)域物流（英文）

1、TSINGHUA SCIENCE AND TECHNOLOGY I S S N 1 0 0 7 - 0 2 1 4 2 2 / 2 3 p p 2 6 5 - 2 6 9 V o l u m e 1 0 , N u m b e r 2 , A p r i l 2 0 0 5 Area Logistics System Based on System Dynamics Model* GUI Shouping (*MW,

2、ZHU Qiang ?£), LU Lifang (P area logistics system; simulation Introduction With China's entry into WTO, modern logistics sys-tems are indispensable for fast economic growth and increased market opening. Ration

3、al area logistics sys-tems 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 effect

4、ive research on area logis-tics problems with few research methods available. Large complicated systems, such as social and eco-nomic systems, can be more effectively analyzed using the system dynamics method. The system

5、 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 syst

6、ems 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 Received: 2003-09-23; revised: 2004-04-12 * Supported by the Natio

7、nal Natural Science Foundation of China (No. 50078024) * * To whom correspondence should be addressed. E-mail: spgui@21cn.net; Tel: 86-20-87111030-3502 data but the model design. The advantage of system dynamics models i

8、s that they include decision trees with consequence and structure, which is the reason why other methods (i.e., econometrics, operational re-search and analysis of input and output) are not as ef-fective as the system dy

9、namics model in analyzing so-cial and economic systems[ 1 _ 5 ]. This paper describes an area logistics model by us-ing qualitative and quantitative system dynamics analyses. The information gathered was used to ana-lyze

10、 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 gi

11、ven 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 expecte

12、d 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]. GUI Shouping fä ^-f-) et al

13、: Area Logistics System Based on System Dynamics Model 267 3 Mathematic Description Fig. 3 System dynamics model for an area logistics system logistics difference; ALC: actual logistics cost; LR: lo-gistics requi

14、rement; GRLD: logistics demand growth rate; BRLD: logistics demand baffle rate; DC: demand coefficient; LC: logistics cost; IFLC: logistics cost in-fluence factor; CF: cost factor; LA: logistics ability; GRLA: logistic a

15、bility growth rate; DLA: logistic abil-ity dissipative rate; IE: investment effect; LI: logistics investment; IFI: investment influence factor; DCL: lo-gistics dissipative coefficient; IED: investment effect delay; CRI:

16、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 X GCGP; BRL = NGR

17、E X BFC (DD/ILC); LD=ALC - ILC; DD=DELAY3 (LD, delay time); ILC=LDXthe chart of IC; LD = INTEG (GRLD - BRLD); GRLD = GDP X the form of DC (LA / LD); BRLD = GRLD X influential factors chart of LC; LA = INTEG (GRLA - DRLA)

18、; GRLA = LA X SGC + the delay of IE X CRI; DLA = LAX DCL; LI = GDP X the form of RI (DD / ILC). The DYNAMO equations for the other variables can be expressed in the same way. The system includes state variables (xi, x 2,

19、 xm), control variables (u\, u2, ur), and the output vari-ables that are related by a system of m first-order dif-ferential equations [ 1' 9' 1 0 ]: Xj = f i ( X j , x 2 , . . . , x m j W j j ^ v j ^ ^ O ? i

20、1 ?2,..., ifi. The output characteristics are expressed as y} = gj(x1,X2,»>,xm',u1,u2,...,ur;t), 7 = 1,2,..., h. Define xx ux x = x2 , u = u2 , Y = _Xm _ u X represents the state vector, U represents t

21、he con-trol vector, and Y represents the output vector. The vector function: fiX, U, t) is the state equation, X^ Rm, Rr; g(X, U, t) is the output equation, Y^Rh. The area logistics system is a feedback system with thre

22、e level variables. The dynamics equations for the vectors can be formulated as: 0 0 L = AL, f o ( ^ 2 2 _ (C 3 4-1)C 3 where L^Rm, A is the transfer matrix, C\2 repre-sents the baffle factor, Cu represents the differe

23、nce de-lay, Cu represents the ideal logistics cost, C2\ repre-sents the demand coefficient, C22 represents the logis-tics cost influential factor, C 3 1 represents the natural growth coefficient, and C 3 4 represents the

24、 dissipative coefficient. The mathematical model with initial values of the system state variables was solved using the simulation software Vensim to calculate the dynamic system changes with time. 4 Model Simulation an