Managing Risks of Supply-Chain Disruptions: Dual ... - CiteSeerX

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------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ Constants Subprogram ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------function [CONSTANTS] = constant% Project lifetimeCONSTANTS.Tlife_y = 15; [years]% Number of periods considered from t=0 to t=Project lifetimeCONSTANTS.num_period=15;% Duration of disruptionCONSTANTS.d =2; [in years/num_period]% Initial Value of DemandCONSTANTS.bintree_init=10;% Loss of market share per year of disruptionCONSTANTS.c=0; [in % market share/year]% DiscountRateCONSTANTS.r=0.05;% Probability of rare eventsCONSTANTS.lambda=0.5;% Volatility of demandCONSTANTS.sigma=0.1;% Drift of the demandCONSTANTS.alpha=0.1;% Price and CostsCONSTANTS.Price=400; [in dollars]CONSTANTS.CostMainSupplier=300; [in dollars]CONSTANTS.CostLocalSupplierOnly=340; [in dollars]CONSTANTS.CostLocalSupplierDualContractNormal=350; [in dollars]CONSTANTS.CostLocalSupplierDualContractDisruption=360; [in dollars]% Percentage of production given to Local SupplierCONSTANTS.PercentageLocalSupplier=0.1;% Investments to change of supplier structureCONSTANTS.OnetoTwo=0;CONSTANTS.OnetoThree=0;CONSTANTS.TwotoOne=0;CONSTANTS.TwotoThree=0;CONSTANTS.ThreetoOne=0;CONSTANTS.ThreetoTwo=0;% Supplemental cost of having two suppliersCONSTANTS.FixedCostTwoSuppliers=0;90
% Delay Local Production when disruptionCONSTANTS.Delay=0; [in % of production/period]---------------------------------------------------------------------------------------------------------------------------------------------------------------------- GENERATION OF BINOMIAL TREE -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------function [TREE] = GenBinTree(CONSTANTS)% Period lengthd_t= CONSTANTS.Tlife_y/CONSTANTS.num_period;TREE.dt = d_t;% Variation of revenues at each periodd_Y = sqrt(CONSTANTS.sigma^2*d_t + (CONSTANTS.alpha-CONSTANTS.sigma^2/2)^2*d_t^2);% Probability of a step upstep_up_p = 0.5 * (1 + (CONSTANTS.alpha-CONSTANTS.sigma^2/2)*d_t/d_Y);TREE.step_up_p = step_up_p;% Values at the end point which is the decision point (possible values of X at decision point)TREE.Y(1,1)= CONSTANTS.bintree_init;for k=2:1:CONSTANTS.num_period +1TREE.K(k) = (k-1)*d_t;for m=1:1:kTREE.Y(m,k) = TREE.Y(1,1) + (k-1)*d_Y - 2*(m-1)*d_Y;endendfor k=1:1:CONSTANTS.num_period+1for m=k+1:1:CONSTANTS.num_period+1TREE.Y(m,k) = NaN;endendTREE.X = exp(TREE.Y);--------------------------------------------------------------------------------------------------------------------------------------------------------------------- GENERATION OF NORMAL PROBA -----------------------------------------------------------------------------------------------------------------------------------------------------------------------------function [NormalProba] = GenNormalProba(CONSTANTS,TREE)% Period lengthd_t= CONSTANTS.Tlife_y/CONSTANTS.num_period;NormalProba.dt = d_t;% Probability of going from (m,k,j)/normal to (m,k+1,j)/normalNormalProba.P1=(1-CONSTANTS.lambda(1)*d_t)*TREE.step_up_p;% Probability of going from (m,k,j)/normal to (m,k+1,j)/disruptionNormalProba.P2=CONSTANTS.lambda(1)*d_t*TREE.step_up_p;91
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Managing Risks of Supply-Chain Disr
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AcknowledgementsI would like to exp
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4.2.5 Conclusions .................
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List of FiguresFigure 1.1: Strategy
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Chapter 1Introduction.Modern supply
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- Levels 2 and 3--between these two
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5. In terms of implementation, Forr
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Some articles focus precisely on di
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2.3 Secure the Supply-ChainThere ar
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1) Firms need to build a resilient
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at ports and airports and along the
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2.6 Conclusions- Increase the secur
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The most adapted approach (single V
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suppliers’. The main objective of
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Some people continue to think that
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For example, there is no market for
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4.1.3 Option ValueJust like a finan
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- I0: initial investmentThe problem
Page 39 and 40: Re plicating portfolio in the up st
Page 41 and 42: Let’s consider a portfolio compri
Page 43 and 44: The differential equation is quite
Page 45 and 46: value of the cash flows of the proj
Page 47 and 48: update their option management stra
Page 49 and 50: Chapter 5OptionModeling Dual-Sourci
Page 52 and 53: We will describe the firm’s curre
Page 54 and 55: investment costs are denotedIMainSu
Page 56 and 57: 5.4 Programming on MatlabTo solve t
Page 58 and 59: Chapter 6Results of the ModelThis c
Page 60 and 61: uses the main supplier its profits
Page 62 and 63: drivers - in particular at the time
Page 64 and 65: what will happen. To hedge this dem
Page 66 and 67: 6.5 Conclusions- Real options allow
Page 68 and 69: market share from its competitor.7.
Page 70 and 71: = 0.99 * ($100) + 0.01* (-$200)= $9
Page 72 and 73: Table 7.1: Assumption on Parameter
Page 74 and 75: 7.2.4 Exploit at maximum real optio
Page 76 and 77: developed “ a general simulation
Page 78 and 79: (13) Lee, H.L., Wolfe, M. (2003),
Page 80 and 81: and Supply Management Course.(38) Z
Page 82 and 83: to reserve for the future, by maxim
Page 84 and 85: APPENDIX B: PARAMETER VALUES USED T
Page 86 and 87: normal or in disruption.The program
Page 88 and 89: -----------------------------------
Page 92 and 93: % Probability of going from (m,k,j)
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Page 96 and 97: -----------------------------------
Page 98 and 99: elsevalue.DecOneNormal=3;end-------
Page 100 and 101: -----------------------------------
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