Order picker routing with product returns and interaction delays

Abstract

E-commerce companies often use manual order-picking systems in their warehouses since these systems can provide the required flexibility and scalability. Manual systems have been widely studied, but the operating policies may require significant changes for e-commerce settings. First, to maintain consumers' loyalty, it is important to maintain delivery reliability even on the busiest days. When the number of order pickers in an area increases, however, more delays due to interactions may occur. For example, travel speed may need to be lowered when order pickers pass each other in narrow aisles. Second, many products sold through e-commerce are returned by consumers. Before these returned products can be sold again, they must be reintegrated in the stock. This paper presents hybrid genetic algorithms to determine routes for simultaneous pickup of products in response to consumers' orders and delivery of returned products to storage locations. Furthermore, interactions between the order pickers are considered in the routing decisions. The developed algorithms use specific warehouse problem characteristics. We identify the mix of pickups and deliveries to realise the highest savings in practice. It is shown that order-picker interactions can be a significant cause for delay and should be accounted for in the routing.

Impact of Digitalization on Customers’ Well-Being in the Pandemic Period: Challenges and Opportunities for the Retail Industry

“…Customers who are under financial pressure also find ways to reverse some of their expenses. Due to the current uncertainty, there are likely to be more returns, so it is essential to provide return processes as non-bureaucratic as possible [ 50 , 51 , 52 ]. If possible, even allow the registration of returns through the web shop and follow the process itself.…”

“…Other online commerce issues refer to the delivery period and the mismatch between the product received and the specification of the product online [ 48 , 52 , 54 ]. To achieve a higher prevalence of m-commerce, certain conditions might be fulfilling, and one of the most important is the development of logistics capabilities and services [ 46 , 55 ].…”

Barriers in omnichannel retailing returns: a conceptual framework

“…In addition to these steps, for the description of the barriers, a backward search was also performed and, thus, three more papers were added to the portfolio. These are Gibson et al (2016) and Wollenburg et al (2018a, b), both quoted by Andersson and Wictor (2018), and Schrotenboer et al (2017), quoted by He et al . (2019).…”

A Discrete Particle Swarm Optimization to Solve the Put-Away Routing Problem in Distribution Centres

“…Although the PRP presents some similarities with picking operations, they have differences in their objective function, decision variables, and constraints. Regarding the objective function and decision variables in the picking routing problem, these functions aim to find the shortest possible operation time, minimum tardiness and maximum level of customer service since they are oriented to outbound logistics in supply chains [34][35][36]. The order picking is constrained by the availability of inventory while the operation is executed, while the PRP is constrained by storage locations in the rack system.…”