An Asymmetric Polling-Based Optimization Model in a Dynamic Order Picking System

The timeliness of order deliveries seriously impacts customers’ evaluation logistics services and, hence, has increasingly received attention. Due to the diverse and large quantities orders under background electronic commerce, how pick efficiently while also adapting these features become one most challenging problems for distribution centers. However, previous studies have not accounted differences in stochastic characteristics generation, which may lead asymmetric optimization problems. With this mind, a new polling-based model that assumes varying analyze such picking systems is put forward. In addition, two important indicators system, mean queue length (MQL) waiting time (MWT), are derived by using probability-generating functions embedded Markov chain. Then, simulation experiments comparison numerical theoretical results conducted, showing usefulness practicalities proposed model. Finally, paper discusses novel system influence MQL MWT on it.