The data you have is stored in a weird manner.
whos
Name Size Bytes Class Attributes
ans 1x40 80 char
cmdout 1x33 66 char
final_best_p_worker 9x5 169560 cell
169560 bytes for a 9x5 cell, Hmmm.
final_best_p_worker
final_best_p_worker =
{1×16 cell} {1×16 cell} {1×16 cell} {1×16 cell} {1×16 cell}
{1×16 cell} {1×16 cell} {1×16 cell} {1×16 cell} {1×16 cell}
{1×16 cell} {1×16 cell} {1×16 cell} {1×16 cell} {1×16 cell}
{1×16 cell} {1×16 cell} {1×16 cell} {1×16 cell} {1×16 cell}
{1×16 cell} {1×16 cell} {1×16 cell} {1×16 cell} {1×16 cell}
{1×16 cell} {1×16 cell} {1×16 cell} {1×16 cell} {1×16 cell}
{1×16 cell} {1×16 cell} {1×16 cell} {1×16 cell} {1×16 cell}
{1×16 cell} {1×16 cell} {1×16 cell} {1×16 cell} {1×16 cell}
{1×16 cell} {1×16 cell} {1×16 cell} {1×16 cell} {1×16 cell}
Each cell element consists a 1x16 cell.
And then each cell element consists a column vector.
There is one uniformity we can work i.e. the total number of elements for each cell element is same (250), so it is possible to vertically concatenate.
for k=1:numel(final_best_p_worker)
y(k)=sum(cellfun('length',final_best_p_worker{k}));
So final product from each cell element will be 250x1 -
for k=1:numel(final_best_p_worker)
final_best_p_worker{k} = vertcat(final_best_p_worker{k}{:});
final_best_p_worker
final_best_p_worker =
{250×1 double} {250×1 double} {250×1 double} {250×1 double} {250×1 double}
{250×1 double} {250×1 double} {250×1 double} {250×1 double} {250×1 double}
{250×1 double} {250×1 double} {250×1 double} {250×1 double} {250×1 double}
{250×1 double} {250×1 double} {250×1 double} {250×1 double} {250×1 double}
{250×1 double} {250×1 double} {250×1 double} {250×1 double} {250×1 double}
{250×1 double} {250×1 double} {250×1 double} {250×1 double} {250×1 double}
{250×1 double} {250×1 double} {250×1 double} {250×1 double} {250×1 double}
{250×1 double} {250×1 double} {250×1 double} {250×1 double} {250×1 double}
{250×1 double} {250×1 double} {250×1 double} {250×1 double} {250×1 double}
After this, you have 3 options how do you want your final data to be stored -
out1 = cell2mat(final_best_p_worker)
out1 =
208 211 158 113 50
115 67 250 26 199
133 223 100 140 181
197 196 146 107 130
174 1 117 57 121
41 77 19 16 10
104 198 51 168 4
113 189 93 96 1
70 59 44 108 171
192 121 191 127 63
out2 = horzcat(final_best_p_worker{:})
out2 =
208 235 57 206 6 205 49 74 14 211 67 149 20 178 238 92 7 159 158 82 225 153 35 66 148 27 29 113 150 4
115 165 65 221 106 193 91 109 59 67 160 7 69 105 20 201 196 232 250 156 186 85 241 75 3 108 153 26 192 140
133 8 4 90 159 180 32 43 179 223 70 236 39 179 235 184 172 193 100 232 3 109 181 212 35 250 83 140 123 236
197 174 232 32 72 148 28 169 10 196 102 231 162 40 100 146 182 20 146 64 188 149 60 54 101 196 221 107 145 66
174 180 109 178 176 62 156 12 230 1 248 16 230 109 156 123 203 51 117 119 240 97 37 74 178 162 12 57 153 163
41 79 207 98 32 211 53 96 231 77 115 144 172 241 66 126 112 189 19 68 226 235 26 61 116 127 208 16 10 154
104 164 27 250 70 248 162 128 145 198 150 203 137 47 248 197 14 150 51 123 163 24 162 185 181 197 210 168 223 185
113 41 202 94 182 28 11 134 11 189 152 221 197 221 197 199 195 9 93 8 69 172 56 223 124 1 15 96 1 15
70 231 189 121 39 186 121 203 155 59 11 193 208 156 208 22 132 4 44 90 203 52 52 131 33 61 154 108 4 119
192 56 234 231 155 92 182 224 157 121 234 58 46 41 56 238 184 75 191 227 147 22 14 56 186 5 62 127 228 53
out3 = vertcat(final_best_p_worker{:})
out3 =
208
115
133
197
174
41
104
113
70
192
Choose whichever size you want to save your data as and use that variable as input to xlswrite() -
xlswrite('matrix.xlsx',array_you_want_to_save)
