# Lec 8 - Because there is a finite number, we may be able to...

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Lecture 8 Team 8 09/27/10 Jewon Kim, Angel Lam, Han Givens, Linh Tran, Isabella Yamin 1. Euclidean Distance Min Computation problem: so pick an initial value 2. Metropolitan Distance Min take derivative m i # of iterations where *reiterate until the values stabilize. After 6 iterations P-median Problem (heuristics vs. algorithms) - Demand point R e t a i l e r l o c a t i o n Min. total travel distance Possible candidate locations Inputs: h i = demand at node i d ij = distance between i and candidate site j J = set of candidate locations I = set of demand nodes P = # of facilities

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Unformatted text preview: Because there is a finite number, we may be able to loop through everything, but complicated and takes a long time Method 2: Decision Variables: X j = 1 locate a facility at j 0 o.w. Y ij = 1 assign node i to j 0 o.w. weight OBJECTIVE FUNCTION Subject to make sure you dont assign consumers to stores that are unoperated every customer is served NP-hard nondeterministic O ( n ) N 1 (size of model) 10 x N 1 1000N 1 O ( n 2 ) N 2 3.16 x N 2 31.6N 2 O ( e n ) N 3 N 3 + 2.30 N 3 + 6.91 speed = 1 speed = 10 speed=1000...
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Lec 8 - Because there is a finite number, we may be able to...

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