Clustering techniques for stock location and order-picking in a distribution
Computers and Operations Research - Special issue on aggregation and disaggregation in operations research
| Hi-index | 0.00 |
The new market forces have affected the operation of distribution centers (DCs) extremely. The DCs demand an increased productivity and a low cost in their daily operation. This paper focuses on the order-picking operation, which is the core operation of DCs, to improve the material-handling process and enhance the competitiveness. The study applied an integrated framework that combined two algorithms, branch-and-bound and tabu search, to the order-picking problem and developed a neighborhood selection criterion based on constraint propagation and the prune-and-search algorithm to improve computational efficiency. The proposed method forbids bad node when searching a solution by branch-and-bound algorithm or tabu search. Besides, in order to make the algorithm more robust and reasonable, the fuzzy modeling was employed. The empirical result shows the approach decreases the computational effort effectively on the both algorithms. The study may be of interest for the researchers in the optimization of DCs' operations and the DCs' managers.