本研究探討IC封裝廠物料揀貨作業之訂單批次處理與揀貨路徑安排的問題，並發展出適合內部揀貨批次與最少揀貨旅行成本的揀貨路徑，以解決倉儲中心揀貨作業重工、過多揀取品項的揀貨單導致長時間的揀貨作業，與不必要的作業等待與揀貨移動時間，以提高物料揀取作業的效率，縮短發料時效。
本研究將此揀貨問題規劃為有容量限制之車輛排程問題 (Capacitated Vehicle Routing Problem, CVRP)，將每一位揀貨員視為一輛有容量限制的車輛，必須用最少的車輛、效率最高的方式，將所有工廠的需求量完成，並以原啟發式演算法 (metaheuristics) - 禁忌搜尋法求解CVRP 問題。以四種求解策略求解個案公司之材料揀貨作業問題，並在不改變現有的倉儲佈局與存儲規則下，開發材料揀貨之最佳策略。
經過系統模擬實驗，證實本演算法皆有很好的績效表現，對於現在企業的揀貨問題，具實際應用價值。本演算法以符合倉儲中心實際揀貨環境，結合材料揀取的載具容積，計算出最佳揀貨批次與揀貨路徑，在揀貨總時間最少的情況下完成揀貨作業。而在總揀貨人次上，四種策略也較未經過運算的派工人次與揀貨員人數有很好的表現，有效節省旅行次數，對於現場作業人員的調度，提供了更大的彈性。本研究開發出之最佳揀貨策略演算法，可提升揀貨效率與降低發料時效，並提高企業生產力與整體生產效益。

This study investigates the material picking issues in an IC assembly factory. The main goals are to develop the picking path, to evaluate the minimum picking travel costs to address the rework of picking operations in the warehouse center, to avoid picking orders with too many items, and to remove unnecessary picking movement waste.
The problem is formulated as a Capacitated Vehicle Routing Problem (CVRP). Each picking operator is considered as a vehicle with capacity constraint. We attempt to complete the material picking requirement with the fewest number of operators/vehicles. To solve the resulting program, we develop a metaheuristics-tabu search. With the proposed solution method, we evaluate four different material picking strategies with real-world data.
Based on the numerical experiment, the results confirmed that the algorithm on these experiments outperforms the factory’s current practice and results in significant savings. On the other hand, the current enterprise met material picking issues, which proves that it possesses practical application value. This algorithm is not only based on a warehouse’s real picking environment but also combines the capacity of the material picking carrier to calculate and optimize the best choice of picking batch and picking route. The algorithm is built on the fewest total working hours to fulfill the picking process. Based on the total picking person-times, that performance is better than those without computed. It could save travel times and provide more flexible men deployment to supervisors. From this research, the development of the best strategy algorithm can improve working efficiency, reduce material delivery times, increase the enterprise’s productivity.

Bramel, J. and D. Simchi-Levi (1997). The logic of logistics: theory, algorithms, and applications for logistics management, Springer New York.
Brynzér, H. and M. I. Johansson (1996). "Storage location assignment: Using the product structure to reduce order picking times." International Journal of Production Economics 46: 595-603.
Caron, F., G. Marchet and A. Perego (2000). "Layout design in manual picking systems: a simulation approach." Integrated Manufacturing Systems 11(2): 94-104.
De Koster, M., E. S. Van der Poort and M. Wolters (1999). "Efficient orderbatching methods in warehouses." International Journal of Production Research 37(7): 1479-1504.
De Koster, R. and E. Van Der Poort (1998). "Routing orderpickers in a warehouse: a comparison between optimal and heuristic solutions." IIE transactions 30(5): 469-480.
Elsayed, E., M.-K. Lee, S. Kim and E. Scherer (1993). "Sequencing and batching procedures for minimizing earliness and tardiness penalty of order retrievals." The International Journal of Production Research 31(3): 727-738.
Elsayed, E. A. and O. Unal (1989). "Order batching algorithms and travel-time estimation for automated storage/retrieval systems." The International Journal of Production Research 27(7): 1097-1114.
Eynan, A. and M. J. Rosenblatt (1994). "Establishing zones in single-command class-based rectangular AS/RS." IIE transactions 26(1): 38-46.
Gendreau, M., A. Hertz and G. Laporte (1994). "A tabu search heuristic for the vehicle routing problem." Management science 40(10): 1276-1290.
Gibson, D. R. and G. P. Sharp (1992). "Order batching procedures." European Journal of Operational Research 58(1): 57-67.
Glover, F. (1986). "Future paths for integer programming and links to artificial intelligence." Computers & operations research 13(5): 533-549.
Glover, F. and M. Laguna (1998). Tabu search. Handbook of combinatorial optimization, Springer: 2093-2229.
Goetschalckx, M. and H. Donald Ratliff (1988). "Order picking in an aisle." IIE transactions 20(1): 53-62.
Goetschalckx, M. and H. D. Ratliff (1988). "An efficient algorithm to cluster order picking items in a wide aisle." Engineering Costs and Production Economics 13(4): 263-271.
Golden, B. L., S. Raghavan and E. A. Wasil (2008). The vehicle routing problem: latest advances and new challenges, Springer Science & Business Media.
Hausman, W. H., L. B. Schwarz and S. C. Graves (1976). "Optimal storage assignment in automatic warehousing systems." Management science 22(6): 629-638.
Kelle, P. and P. A. Miller (2001). "Stockout risk and order splitting." International Journal of Production Economics 71(1-3): 407-415.
Laporte, G. (1992). "The traveling salesman problem: An overview of exact and approximate algorithms." European Journal of Operational Research 59(2): 231-247.
Lawler, E. L. (1985). "The traveling salesman problem: a guided tour of combinatorial optimization." Wiley-Interscience Series in Discrete Mathematics.
Le-Duc, T. and R. B. De Koster (2005). "Travel distance estimation and storage zone optimization in a 2-block class-based storage strategy warehouse." International Journal of Production Research 43(17): 3561-3581.
Nair, D., H. Grzybowska, Y. Fu and V. Dixit (2017). "Scheduling and routing models for food rescue and delivery operations." Socio-Economic Planning Sciences.
Petersen, C. G. (1997). "An evaluation of order picking routeing policies." International Journal of Operations & Production Management 17(11): 1098-1111.
Petersen, C. G. and R. W. Schmenner (1999). "An evaluation of routing and volume‐based storage policies in an order picking operation." Decision Sciences 30(2): 481-501.
Rego, C. (1998). "A subpath ejection method for the vehicle routing problem." Management Science 44(10): 1447-1459.
Roodbergen, K. J. and R. Koster (2001). "Routing methods for warehouses with multiple cross aisles." International Journal of Production Research 39(9): 1865-1883.
Rosenwein, M. B. (1994). "An application of cluster analysis to the problem of locating items within a warehouse." IIE transactions 26(1): 101-103.
Seyyedhasani, H. and J. S. Dvorak (2017). "Using the Vehicle Routing Problem to reduce field completion times with multiple machines." Computers and Electronics in Agriculture 134: 142-150.
Tsai, C.-Y., J. J. Liou and T.-M. Huang (2008). "Using a multiple-GA method to solve the batch picking problem: considering travel distance and order due time." International Journal of Production Research 46(22): 6533-6555.
Vaughan, T. (1999). "The effect of warehouse cross aisles on order picking efficiency." International Journal of Production Research 37(4): 881-897.
Yu, M. and R. B. De Koster (2009). "The impact of order batching and picking area zoning on order picking system performance." European Journal of Operational Research 198(2): 480-490.
Zhang, J. and Z. Zhang (2012). Multi-parameter Multi-objective Algorithm to Solve VRP. Communications and Information Processing, Springer: 156-162.
Zhang, Z., S. Schwartz, L. Wagner and W. Miller (2000). "A greedy algorithm for aligning DNA sequences." Journal of Computational biology 7(1-2): 203-214.
孫海皎 and 董福慶 (1995). 物流中心儲位管理, 經濟部商業自動化系列叢書.
崔利群 and 谢群英 (2006). 现代超市物流与配送, 北京: 经济管理出版社.
羅國書 (2001). 電子零售商的最佳化貨品揀取; Optimizing Order Picking in an e-Tailer Company, 國立中央大學圖書館.