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### Highlights from Traveling Salesman Problem - Nearest Neighbor

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# Traveling Salesman Problem - Nearest Neighbor

### Joseph Kirk (view profile)

02 Sep 2008 (Updated )

Finds a near-optimal solution to a TSP using Nearest Neighbor (NN)

File Information
Description

TSP_NN Traveling Salesman Problem (TSP) Nearest Neighbor (NN) Algorithm
The Nearest Neighbor algorithm produces different results depending on
which city is selected as the starting point. This function determines
the Nearest Neighbor routes for multiple starting points and returns
the best of those routes
Summary:
1. A single salesman travels to each of the cities and completes the
route by returning to the city he started from
2. Each city is visited by the salesman exactly once

Input:
USERCONFIG (structure) with zero or more of the following fields:
- XY (float) is an Nx2 matrix of city locations, where N is the number of cities
- DMAT (float) is an NxN matrix of point to point distances/costs
- POPSIZE (scalar integer) is the size of the population (should be <= N)
- SHOWPROG (scalar logical) shows the GA progress if true
- SHOWRESULT (scalar logical) shows the GA results if true
- SHOWWAITBAR (scalar logical) shows a waitbar if true

Input Notes:
1. Rather than passing in a structure containing these fields, any/all of
these inputs can be passed in as parameter/value pairs in any order instead.
2. Field/parameter names are case insensitive but must match exactly otherwise.

Output:
RESULTSTRUCT (structure) with the following fields:
(in addition to a record of the algorithm configuration)
- OPTROUTE (integer array) is the best route found by the algorithm
- MINDIST (scalar float) is the cost of the best route

Usage:
tsp_nn
-or-
tsp_nn(userConfig)
-or-
resultStruct = tsp_nn;
-or-
resultStruct = tsp_nn(userConfig);
-or-
[...] = tsp_nn('Param1',Value1,'Param2',Value2, ...);

Example:
% Let the function create an example problem to solve
tsp_nn;

Example:
% Request the output structure from the solver
resultStruct = tsp_nn;

Example:
% Pass a random set of user-defined XY points to the solver
userConfig = struct('xy',10*rand(50,2));
resultStruct = tsp_nn(userConfig);

Example:
% Pass a more interesting set of XY points to the solver
n = 100;
phi = (sqrt(5)-1)/2;
theta = 2*pi*phi*(0:n-1);
rho = (1:n).^phi;
[x,y] = pol2cart(theta(:),rho(:));
xy = 10*([x y]-min([x;y]))/(max([x;y])-min([x;y]));
userConfig = struct('xy',xy);
resultStruct = tsp_nn(userConfig);

Example:
% Pass a random set of 3D (XYZ) points to the solver
xyz = 10*rand(50,3);
userConfig = struct('xy',xyz);
resultStruct = tsp_nn(userConfig);

Example:
% Turn off the plots but show a waitbar
userConfig = struct('showProg',false,'showResult',false,'showWaitbar',true);
resultStruct = tsp_nn(userConfig);

Required Products MATLAB
MATLAB release MATLAB 8.3 (R2014a)
26 May 2014 Binayak dutta

### Binayak dutta (view profile)

The code is amazing. The coder is a life saver. But please tell me how to specify the xy coordinates in the code as I'm a novice in matlab. Please!!!!

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12 May 2014 Thomas

### Thomas (view profile)

20 Jan 2014 Julien

### Julien (view profile)

@Joseph: OK it works fine. I was not sure wich coordinates to use in XY.

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09 Dec 2013 Joseph Kirk

### Joseph Kirk (view profile)

@Julien, it is already generalized (other than the figure displays, which you can turn off). Regardless of the dimensionality, the cost/distance matrix will be NxN, and it is this matrix that the algorithm operates on. So the algorithm really is agnostic to the number of dimensions.

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06 Dec 2013 Julien

### Julien (view profile)

Thanks for the algorithm! It works very well.
Are you planning to implement it with higher dimensions ? N=4,5,6 ...

01 Aug 2010 Maroag

### Maroag (view profile)

Pretty nice program. However, there is a small bug in line 103 when by any chance two points are at the same distance min_d. Easily solvable though by just adding a line to choose the first element of J in case length(J)>1. Otherwise, works flawlessly.

18 Jan 2009 Sandip Vijay

### Sandip Vijay (view profile)

16 Oct 2008 Kururunfa Goju

Very nice. It could benefit from the fact of working with TSPLIB files...

02 Jun 2009