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

Info iconThis preview shows pages 1–2. Sign up to view the full content.

View Full Document Right Arrow Icon
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
Background image of page 1

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
Method 1:
Background image of page 2
This is the end of the preview. Sign up to access the rest of the document.

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...
View Full Document

This document was uploaded on 02/01/2012.

Page1 / 2

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

This preview shows document pages 1 - 2. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online