Abstract
In a business-to-consumer (B2C) context, customers order more frequently and in smaller quantities, resulting in a high number of consignments. Moreover, online shoppers expect a fast and accurate delivery at low cost or even free. To survive in such a market, companies can no longer optimise individual supply chain processes, but need to integrate several activities. In this article, the integrated order picking-vehicle routing problem is analysed in an e-commerce environment. In previous research, a mathematical programming formulation has been formulated in literature but only small-size instances can be solved to optimality. Two picking policies are studied: discrete order picking and batch order picking. The influence of various problem contexts on the value of integration is investigated: a small picking time period, outsourcing to 3PL service providers, and a dynamic environment context.
Highlights
Production and distribution are two functions in a supply chain
One might think of vehicle routing problems, which appear in many variants
This paper is the first step towards research on integrated order picking-vehicle routing problems with a batch picking policy
Summary
Production and distribution are two functions in a supply chain. In both functions, decisions need to be taken and optimization models emerge. One way to reduce travel times is to implement a batch picking policy in which multiple customer orders are combined into a single route. The order picker has to travel the route through the warehouse only once In this example, the picking time with batch picking is approximately half of the picking time compared with a discrete order picking policy. A disadvantage of batch picking is that items of different customer orders need to be sorted when they are picked in the same route. An integrated problem applying a batch picking strategy is compared with one using a discrete picking policy. This paper is the first step towards research on integrated order picking-vehicle routing problems with a batch picking policy. The goal is to identify what the effect is of a batch picking policy in specific circumstances on the value of integration
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