| dc.description.abstract | Optimization is very useful in almost all fields in running a business
effectively and efficiently to achieve the desired results. This study solves the
problem of multiple constraints bounded knapsack by implementing DOA. The
problem of multiple constraints bounded knapsack has more than ones constraint
with objects that are entered into the storage media, the dimensions can be partially
or completely included, but the number of objects is limited. The purpose of this
study is to determine the results of using DOA to solve multiple constraits bounded
knapsack and the effectiveness of DOA compared to the results of the Simplex
method. The data used in this study are primary data. There are ten parameters to
be tested, namely population parameters, maximum iteration, s, a, c, f, e and range.
The trial results of the ten parameters show that the best value of the parameters is
neither too large nor too small. If the best value is too large then the position of the
dragonfly will be randomized so that it is not clear the position of the dragonfly
and if it is too small the best value then the change is not visible. In addition, based
on the results of the final experiment it can be seen that DOA is less effective in
solving multiple constraints bounded knapsack problems, because of many
experiments there is no solution similar to Simplex. DOA approach to optimal,
seen from a small deviation. | en_US |
