Description
Newsboy problem from Lindo manual Random parameters D and R are discrete and independently distributed Reference: LINDO API 7.0 User Manual
Small Model of Type : SP
Category : GAMS EMP library
Main file : nbdiscindep.gms
$title Newsboy problem, discrete and independent distribution (NBDISCINDEP,SEQ=78)
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Newsboy problem from Lindo manual
Random parameters D and R are discrete and independently distributed
Reference: LINDO API 7.0 User Manual
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Scalar c Purchase costs per unit / 30 /
p Penalty shortage cost per unit unsatisfied demand / 5 /
h Holding cost per unit leftover / 10 /
v Revenue per unit sold / 60 /
* Random parameters
d Demand / 63 /
r Refund per unit / 9 /;
Variable Z Profit;
Positive Variables
X Units bought
I Inventory
L Lost sales
S Units sold
Y Units returned
E Units kept;
Equations Row1, Row2, Row3, Row4, Profit;
* Units bought, X, Buy at least 1 (serves as a dummy constraint for stage 1);
Row1.. X =g= 1;
* Inventory (I) and Lost Sales (L);
Row2.. I =e= X + L - d;
* Units sold S, and inventory left over, I;
Row3.. S =e= X - I;
* Y units returned to vendor for a possible refund, and E kept;
Row4.. Y + E =e= I;
* Profit, to be maximized;
Profit.. Z =e= v*S - c*X - h*I - p*L + r*Y - h*E;
Model nb / all /;
file emp / '%emp.info%' /; put emp '* problem %gams.i%'/;
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randvar d discrete 0.4 90
0.3 60
0.3 30
randvar r discrete 0.7 9
0.3 -15
stage 2 d
stage 3 r
stage 2 I L S
stage 3 Z Y E
stage 2 Row2 Row3
stage 3 Profit Row4
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putclose emp;
Set scen scenarios / s1*s36 /;
Parameter
s_d(scen) demand realization by scenario
s_r(scen) refund realization by scenario
s_x(scen)
s_s(scen) ;
Set dict / scen .scenario.''
d .randvar .s_d
r .randvar .s_r
s .level .s_s
x .level .s_x /;
solve nb max z use emp scenario dict;
display s_d, s_r, s_s, s_x;