Our method is to cut original solution space into many subspaces using objective function before implementing B&B.
It could narrow down the feasible solution range.
After labeling these subspaces based on the ‘‘distance’’ from objective function, we can apply B&B procedure upon subspaces one by one.
The nearest subspace will be the first one to be searched.
The first optimum solution we get in the nearest subspace is promised to be the optimum solution in all solution space because of using objective function.
The procedure of our proposed method is explained below: