This package provides m- and mex-functions for solving the rectangular assignment problem.

assignmentsuboptimal2(distMatrix)

function [assignment, cost] = assignmentsuboptimal2(distMatrix)
%ASSIGNMENTSUBOPTIMAL2 Compute suboptimal assignment
% ASSIGNMENTSUBOPTIMAL2(DISTMATRIX) computes a suboptimal assignment
% (minimum overall costs) for the given rectangular distance or cost
% matrix, for example the assignment of tracks (in rows) to observations
% (in columns). The result is a column vector containing the assigned
% column number in each row (or 0 if no assignment could be done).
%
% [ASSIGNMENT, COST] = ASSIGNMENTSUBOPTIMAL2(DISTMATRIX) returns the
% assignment vector and the overall cost.
%
% The algorithm searches the matrix for the minimum element and makes the
% corresponding row-column assignment. After setting all elements in the
% given row and column to infinity (i.e. forbidden assignment), the
% search procedure is repeated until all assignments are done or only
% infinite values are found.
%
% This function and the corresponding mex-function can further be
% improved by first sorting all elements instead of searching for the
% minimum of all elements many times.
%
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%
% Markus Buehren
% Last modified 05.07.2011
% initialize
nOfRows = size(distMatrix, 1);
assignment = zeros(nOfRows,1);
cost = 0;
for n=1:nOfRows
% find minimum distance observation-to-track pair
[minDist, index1] = min(distMatrix, [], 1);
[minDist, index2] = min(minDist);
row = index1(index2);
col = index2;
if isfinite(minDist)
% make the assignment
assignment(row) = col;
cost = cost + minDist;
% delete observation-to-track pair
distMatrix(row, :) = inf;
distMatrix(:, col) = inf;
else
return
end
end