| dc.description.abstract | In recent years, the rapid development of information technology, coupled with the widespread adoption of mobile networks, has led to the prevalence of e-commerce. Consequently, market demands have shifted towards ＂small quantity and diversity,＂ increasing the complexity of operations in logistics centers, particularly in picking activities. According to the study by De Koster et al. (2007), most logistics centers remain labor-intensive industries. Picking operations are not only costly but also labor-intensive, with related personnel accounting for over 50% of the workforce in these centers. Therefore, to adapt to the era of ＂small quantity and diversity＂ demands, timely introduction of automated equipment and planning an appropriate picking strategy is crucial in significantly impacting the cost, capacity, and efficiency of logistics centers.
Based on the aforementioned reasons, this study aims to delve into the picking strategies in zone-picking warehouses similar to those using LocusBots systems, setting it apart from previous studies on LocusBots systems. We have broken the traditional constraint that pickers can only operate within their designated blocks. In our system, pickers are allowed to assist each other within blocks that belong to their own zone. This study explores the ＂Block Selection Problem for Pickers,＂ proposing two types of rules. The first type, designed in this study, governs the picker′s block selection, while the second type extends the first, aiming to preemptively select busier blocks within their zone for picking. The evaluation method involves calculating the ratio of the number of robots to the number of pickers (R/P ratio) in a picking block. If the ratio exceeds 1, it indicates that the block is busy. Once busy blocks are identified, the first type of block selection rule designed in this research is applied. If there are no blocks with an R/P ratio greater than 1, pickers directly use the first type of block selection rule.
Finally, we utilize the Arena simulation software to experimentally analyze and compare the first and second types of block selection rules and evaluate the performance of the proposed rules under different performance indicators. Through this, we aim to identify the most suitable combination of picking strategies, providing valuable insights and contributions for future similar research. | en_US |