Parking (car Cars[], car Park[0, int Area) { Car Cr, int CrNb; CrNb <-- 0; Park <-- { }; Cr <-- Select (Cars) I// Cr = / if the Cars = {} while (Feasible (Cr)) do { Remove (Cr, Cars); Add (Cr, Park); CrNb <-- CrNb +1; Cr <-- Select (Cars) } if exist-Solution (Park) Then Success else return Error } Trace the above Greedy algorithm with the following data: Area = 1000, Cars [100, 50, 90, 70. 200, 30 400, 80, 200] the cost for each parked car is 3JD. The objective function is: k Max (ΣCis 1000) K |=1

Computer Networking: A Top-Down Approach (7th Edition)
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ISBN:9780133594140
Author:James Kurose, Keith Ross
Publisher:James Kurose, Keith Ross
Chapter1: Computer Networks And The Internet
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Problem R1RQ: What is the difference between a host and an end system? List several different types of end...
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Parking (car Cars[], car Park[], int Area)
{
Car Cr, int CrNb;
CrNb <-- 0;
Park <-- { };
Cr <-- Select (Cars) I/ Cr = / if the Cars = {}
while (Feasible (Cr)) do
{ Remove (Cr, Cars);
Add (Cr, Park);
CrNb <-- CrNb +1;
Cr <-- Select (Cars)
}
if exist-Solution (Park) Then Success
else return Error
}
Trace the above Greedy algorithm with the
following data:
Area = 1000, Cars [100, 50, 90, 70. 200, 300,
400, 80, 200]
the cost for each parked car is 3JD.
The objective function is:
%3D
k
Max (ΣCis 1000)
K
|=1
Transcribed Image Text:Parking (car Cars[], car Park[], int Area) { Car Cr, int CrNb; CrNb <-- 0; Park <-- { }; Cr <-- Select (Cars) I/ Cr = / if the Cars = {} while (Feasible (Cr)) do { Remove (Cr, Cars); Add (Cr, Park); CrNb <-- CrNb +1; Cr <-- Select (Cars) } if exist-Solution (Park) Then Success else return Error } Trace the above Greedy algorithm with the following data: Area = 1000, Cars [100, 50, 90, 70. 200, 300, 400, 80, 200] the cost for each parked car is 3JD. The objective function is: %3D k Max (ΣCis 1000) K |=1
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