A rule-based heuristic algorithm for joint order batching and delivery planning of online retailers with multiple order
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A rule-based heuristic algorithm for joint order batching and delivery planning of online retailers with multiple order pickers Fahimeh Hossein Nia Shavaki 1 & Fariborz Jolai 1
# Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract 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. Keywords Delivery planning . Online retailing . Order batching . Rule-based heuristic algorithm . Specific due dates
1 Introduction Recently, noticeable increase in the use of the internet and improvement of e-commerce has significantly changed the way of shopping, managing activities, and distributing products for individuals and companies [35]. Retailing is one of the industries that has been inextricably affected by these changes. In an e-commerce context of retailing, the number of customer orders increases, however, order size decreases [16]. Therefore, a large number of small orders have to be prepared and delivered to numerous customers in a limited time. In an online system, customer orders become available dynamically [17] and there is no information about future orders. Moreover, customers expect more flexible services from retailers in a competitive market place. Order picking is one of the most costly and critical operations of any retailing system [7]. Order picking is defined as the process of retrieving items of an order from their storage locations. * Fariborz Jolai [email protected] 1
School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran
In systems with large numbers of small orders, order batching methods can reduce order picking process time. Order batching methods group a set of orders into a number of sub-sets, so
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