近年來，由於世界經濟的全球化、貿易的自由化、顧客服務水準的提升等因素，物流已成為全球企業關注的焦點，做好物流工作以降低營運成本、提高顧客服務水準並滿足顧客的要求已經成為企業強化競爭優勢的武器。揀貨作業是最耗費作業量與人力的一環，在傳統物流中心裡，揀貨作業時間佔整體物流時間的30％至40％左右。因此，有效的降低揀貨作業時間與成本，提升商品揀取與處理的作業效率，對於物流中心的營運是有決定性的影響。 本研究環境為順序式分區揀貨（Sequential zone picking），探討的問題著重在揀貨人員之間是否可以進行互助合作來提升整體的揀貨效率，不同揀貨人員會有不同的合作策略，同時分析不同的儲存策略及忙碌程度界限是否對於合作策略有所影響。吾人利用Arena11.0撰寫模擬程式，再以SPSS 12.0進行實驗分析，求得訂單完成的總揀貨時間為最小之合作策略，進而提升揀貨效率。 根據本研究顯示，不同的儲存策略下所對應之最佳的合作策略均有所差異。且本研究所提出之三項因子對於總揀貨時間皆有顯著地影響。 Because of globalization, trade liberalization and the enhancement of customer service level, logistics has become a hot topic to world business. A good logistics skill would help them to reduce operation costs, improve customer service level and raise customer satisfaction. Among logistics technologies, order picking costs the most operation and labor power, the picking time is almost 30-40% of all the logistic operation in the traditional logistic center. Therefore, reducing the time and the cost of picking operation and enhancing the product selection rate effectively would be a critical point to logistics centers. This research will focus on the mutual assistances and the picking efficiency in the sequential zone picking environment, and also analyze the affections to cooperation policies depends on different storage strategies and the levels of busy threshold. We use Arena11.0 and the statistical software SPSS 12.0 to code the simulation and do the analysis, finding the optimal cooperation policy with the fewest picking time. According to this research, we find out that different storage strategies would correspond to different optimal cooperation policies. In addition, the research demonstrates three factors will affect the picking time.
