Niels Agatz

E-fulfillment and multi-channel distribution - A review

This review addresses the specific supply chain management issues of Internet fulfillment in a multi-channel environment. It provides a systematic overview of managerial planning tasks and reviews corresponding quantitative models. In this way, we aim to enhance the understanding of multi-channel e-fulfillment and to identify gaps between relevant managerial issues and academic literature, thereby indicating directions for future research. One of the recurrent patterns in today’s e-commerce operations is the combination of ‘bricks-and-clicks’, the integration of e-fulfillment into a portfolio of multiple alternative distribution channels. From a supply chain management perspective, multi-channel distribution provides opportunities for serving different customer segments, creating synergies, and exploiting economies of scale. However, in order to successfully exploit these opportunities companies need to master novel challenges. In particular, the design of a multi-channel distribution system requires a constant trade-off between process integration and separation across multiple channels. In addition, sales and operations decisions are ever more tightly intertwined as delivery and after-sales services are becoming key components of the product offering.

Optimization for Dynamic Ride-Sharing: A Review

Dynamic ride-share systems aim to bring together travelers with similar itineraries and time schedules on short-notice. These systems may provide significant societal and environmental benefits by reducing the number of cars used for personal travel and improving the utilization of available seat capacity. Effective and efficient optimization technology that matches drivers and riders in real-time is one of the necessary components for a successful dynamic ride-share system. We systematically outline the optimization challenges that arise when developing technology to support ride-sharing and survey the related operations research models in the academic literature. We hope that this paper will encourage more research by the transportation science and logistics community in this exciting, emerging area of public transportation.

Time Slot Management in Attended Home Delivery

Many e-tailers providing attended home delivery, especially e-grocers, offer narrow delivery time slots to ensure satisfactory customer service. The choice of delivery time slots has to balance marketing and operational considerations, which results in a complex planning problem. We study the problem of selecting the set of time slots to offer in each of the zip codes in a service region. The selection needs to facilitate cost-effective delivery routes, but also needs to ensure an acceptable level of service to the customer. We present a fully automated approach that is capable of producing high-quality delivery time slot offerings in a short amount of time. Computational experiments reveal the value of this approach and the impact of the environment on the underlying trade-offs.

The benefits of meeting points in ride-sharing systems

We investigate the potential benefits of introducing meeting points in a ride-sharing system. With meeting points, riders can be picked up and dropped off either at their origin and destination or at a meeting point that is within a certain distance from their origin or destination. The increased flexibility results in additional feasible matches between drivers and riders, and allows a driver to be matched with multiple riders without increasing the number of stops the driver needs to make. We design and implement an algorithm that optimally matches drivers and riders in large-scale ride-sharing systems with meeting points. We perform an extensive simulation study to assess the benefits of meeting points. The results demonstrate that meeting points can significantly increase the number of matched participants as well as the system-wide driving distance savings in a ride-sharing system.

Challenges and opportunities in attended home delivery

In this chapter, we focus on home delivery, and, more specifically, on attended home delivery, where the consumer must be present for the delivery. To provide a high service level and to avoid delivery failures as much as possible, it is customary in attended home delivery services for the company to offer the customer a choice of narrow delivery time slots. The objective of this chapter is to highlight and illustrate issues arising in attended home delivery related to these time slots and to present and discuss promising approaches for addressing some of them. We will use Peapod, one of the more successful e-grocers, as an illustrative example.

Optimization Approaches for the Traveling Salesman Problem with Drone

The fast and cost-effcient home delivery of goods ordered online is logistically challenging. Many companies are looking for new ways to cross the last-mile to their customers. One technology-enabled opportunity that recently has received much attention is the use of a drone to support deliveries. An innovative last-mile delivery concept in which a truck collaborates with a drone to make deliveries gives rise to a new variant of the traveling salesman problem (TSP) that we call the TSP with drone. In this paper, we formulate this problem as an MIP model and develop several fast route first-cluster second heuristics based on local search and dynamic programming. We prove worst-case approximation ratios for the heuristics and test their performance by comparing the solutions to the optimal solutions for small instances. In addition, we apply our heuristics to several artificial instances with different characteristics and sizes. Our numerical analysis shows that substantial savings are possible with this concept in comparison to truck-only delivery.

Stable Matching for Dynamic Ride-Sharing Systems

Dynamic ride-sharing systems enable people to share rides and increase the efficiency of urban transportation by connecting riders and drivers on short notice. Automated systems that establish ride-share matches with minimal input from participants provide the most convenience and the most potential for system-wide performance improvement, such as reduction in total vehicle-miles traveled. Indeed, such systems may be designed to match riders and drivers to maximize system performance improvement. However, system-optimal matches may not provide the maximum benefit to each individual participant. In this paper we consider a notion of stability for ride-share matches and present several mathematical programming methods to establish stable or nearly-stable matches, where we note that ride-share matching optimization is performed over time with incomplete information. Our numerical experiments using travel demand data for the metropolitan Atlanta region show that we can significantly increase the stability of ride-share matching solutions at the cost of only a small degradation in system-wide performance.

Optimization approaches for civil applications of unmanned aerial vehicles (UAVs) or aerial drones

Unmanned aerial vehicles (UAVs), or aerial drones, are an emerging technology with significant market potential. UAVs may lead to substantial cost savings in, for instance, monitoring of difficult-to-access infrastructure, spraying fields and performing surveillance in precision agriculture, as well as in deliveries of packages. In some applications, like disaster management, transport of medical supplies, or environmental monitoring, aerial drones may even help save lives. In this article, we provide a literature survey on optimization approaches to civil applications of UAVs. Our goal is to provide a fast point of entry into the topic for interested researchers and operations planning specialists. We describe the most promising aerial drone applications and outline characteristics of aerial drones relevant to operations planning. In this review of more than 200 articles, we provide insights into widespread and emerging modeling approaches. We conclude by suggesting promising directions for future research.

The Benefits of Meeting Points in Ride-sharing Systems

We investigate the potential benefits of introducing meeting points in a ride-sharing system. With meeting points, riders can be picked up and dropped off either at their origin and destination or at a meeting point that is within a certain distance from their origin or destination. The increased flexibility results in additional feasible matches between drivers and riders, and allows a driver to be matched with multiple riders without increasing the number of stops the driver needs to make. We design and implement an algorithm that optimally matches drivers and riders in large-scale ride- sharing systems with meeting points. We perform an extensive simulation study to assess the benefits of meeting points. The results demonstrate that meeting points can significantly increase the number of matched participants as well as the system-wide driving distance savings in a ride-sharing system.

Autonomous car and ride sharing: flexible road trains: (vision paper)

Since in many cities transport infrastructure is operating at or beyond capacity, novel approaches to organize urban mobility are gaining attraction. However, assessing the benefits of a measure that has disruptive capacity in a complex system requires a carefully designed research. This paper takes a recent idea for urban mobility - flexible road trains - and illustrates the computational and research challenges of realizing its full potential and describing its social, ecological and economical impact.