Bin packing problem examines the minimum number of identical bins needed to pack a set of items of various weights. This problem arises in various areas of the artificial intelligence demanding derivation of the exact solutions in the shortest amount of time. Employing branch-and-bound and column generation techniques to derive the exact solutions to this problem, usually requires designation of problem-specific branching rules compatible with the nature of the polluted pricing sub-problem of column generation. In this work, we present a new approach to deal with the forbidden bins which handles two-dimensional knapsack problems. Furthermore, a set of diving criteria are introduced which emphasize the importance of the geometrical features of the bins. It is further shown that efficiency of the column generation technique could significantly get improved using an implicit sectional pricing scheme. The proposed algorithm outperforms the current state-of-the-art algorithms in number of the benchmark instances solved in less than one minute.