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To validate the proposed model, a small-sized problem was solved with GAMS software.
Hence a small-sized problem is generated by using the uniform distribution, and it is solved with the Lingo 8 software.
In the above example, a small-sized problem is designed and solved for several states and the analysis of the problem is showed model accuracy and performance.
We report that the branch and bound algorithm is more effective than the proposed mathematical formulation which can solve small sized problem.
Also, it finds optimal solutions only for small sized problems using the complete enumeration method and near optimal solutions for real sized problems using evolutionary algorithms.
The computational results for small sized problems show that the mentioned algorithms are fully effective and viable to generate optimal/near optimal solutions, but when the size of the problem is increased, the HPSOGA obtains better results in comparison with other algorithms.
A small sized experimental autonomous bicycle is developed.
Chop up a small sized fresh cucumber into fine pieces.
Take a small sized bucket and get in the tank.
A multi-commodity network flow mixed-integer mathematical program is proposed and applied to small-sized problem instances to validate the model.
The results are given in Table 5. Small-sized problem sets ((left| Jright| =10)) can be easily solved to optimality.
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