Production scheduling and vehicle routing are two well-studied problems in literature. Although these supply chain functions are interrelated, they are often solved sequentially. This uncoordinated approach can lead to suboptimal solutions. In the current competitive business environment, companies are searching for methods to save costs and improve their service level. Integrating production and distribution scheduling operations can be an approach to improve the overall performance. This paper focuses on integrated production-distribution operational level scheduling problems, which explicitly take into account vehicle routing decisions of the delivery process. Existing literature on integrated production scheduling and vehicle routing problems is reviewed and classified. Both the problem characteristics of mathematical models and the accompanying solution approaches are discussed to identify directions for further research.
E-commerce sales are increasing every year and customers who buy goods on the Internet have high service level expectations. In order to meet these expectations, a company's logistics operations need to be performed carefully. Optimizing only internal warehouse processes will often lead to suboptimal solutions. The interrelationship between the order picking process and the delivery process should not be ignored. Therefore, in this study, an order picking problem and a vehicle routing problem with time windows and release dates are solved simultaneously using a single optimization framework. To the best of our knowledge, it is the first time that an order picking problem and a vehicle routing problem are integrated. A mixed integer linear programming formulation for this integrated order picking-vehicle routing problem (OP-VRP) is provided. The integrated OP-VRP is solved for small instances and the results are compared to these of an uncoordinated approach. Computational experiments show that integration can lead to cost savings of 14% on average. Furthermore, higher service levels can be offered by allowing customers to request their orders later and still get delivered within the same time windows.
In B2C e-commerce sales, customers expect a fast and low-cost delivery. To be able to fulfil these customer expectations, both warehouse and distribution operations have to be performed in an efficient and effective way. Ideally, these two supply chain functions should be considered simultaneously in an integrated problem since they are interrelated. In this paper, a record-to-record travel algorithm is proposed to solve the integrated order picking-vehicle routing problem (I-OP-VRP). Experiments with both small-size and large-size instances are conducted. Furthermore, the integrated approach is compared with an approach in which both problems are solved sequentially. Results show that integration leads to increased service levels, i.e., it allows to shorten the time between placing an order and receiving the goods. On top, the integrated approach leads to costs savings of on average 1.8%. Thus, integration is indispensable for a fast and cost-efficient delivery of goods.
European e-commerce sales are increasing every year. Nowadays, customers buy more frequently online in smaller quantities. Handling this large amount of customer orders puts the logistic activities of the supply chain under pressure. At the same time, customers have high expectations concerning the delivery of their online purchase. In order to meet these expectations at low cost, B2C e-commerce companies have to reconsider their logistic activities. Instead of optimizing every single process of the supply chain, related problems need to be tackled simultaneously. In the integrated order picking-vehicle routing problem(I-OP-VRP), picking lists and vehicle routes are determined simultaneously. One possibility to meet the high expectations of customers is to allow customers to choose the time window in which they want to be delivered. However, the more customers select a time window during the purchasing process, the higher the total costs for the B2C e-commerce company since the company has less flexibility to construct their delivery routes. To cover the cost increase, e-commerce companies often only provide this service at an additional cost. The objective of this paper is to estimate the additional cost of allowing customers to choose a preferred delivery time window using the integrated order picking-vehicle routing problem. An experimental design is set up to investigate this service cost under varying circumstances depending on customer characteristics, time window characteristics and operator size. Based on the results of the ANOVA it can be concluded that the investigated factors have a significant influence on the additional cost of allowing customers to select a delivery time window.
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.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.