A rule-based heuristic algorithm for joint order batching and delivery planning of online retailers with multiple order pickers

摘要

Today with the rapid improvement of new technologies, people tend to buy various products from online retailers which facilitate the purchasing process and save their valuable limited time. Two important and interconnected operations of each online retailing system are order picking and delivery planning. In an online system, lots of small orders including different products arrive dynamically and must be delivered on time, so there is a limited time to retrieve products from their storage locations, pack them, load onto trucks, and deliver to the destinations. In this study, we deal with these two problems of an online retailer that stores a variety of products in a warehouse and sells them online through their website. A rule-based heuristic algorithm is proposed which integrates decisions of order batching, picking schedule of batches, and assigning orders to trucks as well as, scheduling and routing of trucks. Three different batching methods including two well- known heuristics and a genetic algorithm have been used. An extensive numerical experiment is carried out to show the efficiency of the rule-based algorithm and investigate the results of using each batching method for different problem sizes. It is demonstrated that while the algorithm has efficient performance with three used batching methods, the genetic algorithm can lead to less system cost and more order pickers productivity.