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solve_raw.m
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function solve_raw()
% A function that solves a set number of instances of online
% concurrent open shop using all combinations of
% algorithms in this repository.
num_instances = 50;
num_algorithms = 3;
N = 500; % Number of jobs
weighted_sums = zeros(num_algorithms, num_instances);
%%%% Sparse instances ------------
%%% max_p >> max_r
% identical weights
load p_i_sparse_raw.mat;
fprintf('\np_i_sparse instances: ');
for j = 1:num_instances
fprintf('%d ', j);
weighted_sums(:, j) = single_instance(p_times(:,:,j), weights(:, j), release_times(:, j), num_algorithms);
end
weighted_sums = mean(weighted_sums, 2);
save p_i_sparse.mat weighted_sums;
clear p_times weights release_times;
% random weights
load p_r_sparse_raw.mat;
fprintf('\np_r_sparse instances: ');
for j = 1:num_instances
fprintf('%d ', j);
weighted_sums(:, j) = single_instance(p_times(:,:,j), weights(:, j), release_times(:, j), num_algorithms);
end
weighted_sums = mean(weighted_sums, 2);
save p_r_sparse.mat weighted_sums;
clear p_times weights release_times;
%%% max_r >> max_r
% identical weights
load r_i_sparse_raw.mat;
fprintf('\nr_i_sparse instances: ');
for j = 1:num_instances
fprintf('%d ', j);
weighted_sums(:, j) = single_instance(p_times(:,:,j), weights(:, j), release_times(:, j), num_algorithms);
end
weighted_sums = mean(weighted_sums, 2);
save r_i_sparse.mat weighted_sums;
clear p_times weights release_times;
% random weights
load r_r_sparse_raw.mat;
fprintf('\nr_r_sparse instances: ');
for j = 1:num_instances
fprintf('%d ', j);
weighted_sums(:, j) = single_instance(p_times(:,:,j), weights(:, j), release_times(:, j), num_algorithms);
end
weighted_sums = mean(weighted_sums, 2);
save r_r_sparse.mat weighted_sums;
clear p_times weights release_times;
%%%% Dense instances ------------
%%% max_p >> max_r
% identical weights
load p_i_dense_raw.mat;
fprintf('\np_i_dense instances: ');
for j = 1:num_instances
fprintf('%d ', j);
weighted_sums(:, j) = single_instance(p_times(:,:,j), weights(:, j), release_times(:, j), num_algorithms);
end
weighted_sums = mean(weighted_sums, 2);
save p_i_dense.mat weighted_sums;
clear p_times weights release_times;
% random weights
load p_r_dense_raw.mat;
fprintf('\np_r_dense instances: ');
for j = 1:num_instances
fprintf('%d ', j);
weighted_sums(:, j) = single_instance(p_times(:,:,j), weights(:, j), release_times(:, j), num_algorithms);
end
weighted_sums = mean(weighted_sums, 2);
save p_r_dense.mat weighted_sums;
clear p_times weights release_times;
%%% max_r >> max_r
% identical weights
load r_i_dense_raw.mat;
fprintf('\nr_i_dense instances: ');
for j = 1:num_instances
fprintf('%d ', j);
weighted_sums(:, j) = single_instance(p_times(:,:,j), weights(:, j), release_times(:, j), num_algorithms);
end
weighted_sums = mean(weighted_sums, 2);
save r_i_dense.mat weighted_sums;
clear p_times weights release_times;
% random weights
load r_r_dense_raw.mat;
fprintf('\nr_r_dense instances: ');
for j = 1:num_instances
fprintf('%d ', j);
weighted_sums(:, j) = single_instance(p_times(:,:,j), weights(:, j), release_times(:, j), num_algorithms);
end
weighted_sums = mean(weighted_sums, 2);
save r_r_dense.mat weighted_sums;
clear p_times weights release_times;
%%%% Uniform instances ------------
%%% max_p >> max_r
% identical weights
load p_i_uniform_raw.mat;
fprintf('\np_i_uniform instances: ');
for j = 1:num_instances
fprintf('%d ', j);
weighted_sums(:, j) = single_instance(p_times(:,:,j), weights(:, j), release_times(:, j), num_algorithms);
end
weighted_sums = mean(weighted_sums, 2);
save p_i_uniform.mat weighted_sums;
clear p_times weights release_times;
% random weights
load p_r_uniform_raw.mat;
fprintf('\np_r_uniform instances: ');
for j = 1:num_instances
fprintf('%d ', j);
weighted_sums(:, j) = single_instance(p_times(:,:,j), weights(:, j), release_times(:, j), num_algorithms);
end
weighted_sums = mean(weighted_sums, 2);
save p_r_uniform.mat weighted_sums;
clear p_times weights release_times;
%%% max_r >> max_r
% identical weights
load r_i_uniform_raw.mat;
fprintf('\nr_i_uniform instances: ');
for j = 1:num_instances
fprintf('%d ', j);
weighted_sums(:, j) = single_instance(p_times(:,:,j), weights(:, j), release_times(:, j), num_algorithms);
end
weighted_sums = mean(weighted_sums, 2);
save r_i_uniform.mat weighted_sums;
clear p_times weights release_times;
% random weights
load r_r_uniform_raw.mat;
fprintf('\nr_r_uniform instances: ');
for j = 1:num_instances
fprintf('%d ', j);
weighted_sums(:, j) = single_instance(p_times(:,:,j), weights(:, j), release_times(:, j), num_algorithms);
end
weighted_sums = mean(weighted_sums, 2);
save r_r_uniform.mat weighted_sums;
clear p_times weights release_times;
end