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.Distribution;E-fulfillment;Literature Review;Online Retailing

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 two fully-automated approaches that are capable of producing high-quality delivery time slot offerings in a reasonable amount of time. Computational experiments reveal the value of these approaches and the impact of the environment on the underlying trade-offs.integer programming;vehicle routing;continuous approximation;e-grocery;home delivery;time slots

Optimisation for dynamic ride-sharing

For decades, people have looked for ways to maximise personal transportation efficiency, especially for the regular commute between home and work. Particularly in times of economic difficulties, the primary aim is generally to reduce costs by sharing them. However, an important priority for travellers by car is also to find a substitute for inadequate public transport

Demand Management Opportunities in E-fulfillment: What Internet Retailers Can Learn from Revenue Management

In this paper, we explain how Internet retailers can learn from proven revenue management concepts and use them to reduce costs and enhance service. We focus on attended deliveries as these provide the greatest opportunities and challenges. The key driver is service differentiation. Revenue management has shown that companies can do much better than a one-size-fits-all first-come-first-serve strategy when selling scarce capacity to a heterogeneous market. Internet retailers have strong levers at their disposal for actively steering demand, notably the offered delivery time windows and their associated prices. Unlike traditional revenue management, these demand management decisions affect both revenues and costs. This calls for a closer coordination of marketing and operations than current common practice.ketenbeheer;revenue management;home delivery;E-fulfillment;demand management;marketing-operations interface

Data analytics and optimization for assessing a ride sharing system

Ride-sharing schemes attempt to reduce road traffic by matching prospective passengers to drivers with spare seats in their cars. To be successful, such schemes require a critical mass of drivers and passengers. In current deployed implementations, the possible matches are based on heuristics, rather than real route times or distances. In some cases, the heuristics propose infeasible matches; in others, feasible matches are omitted. Poor ride matching is likely to deter participants from using the system. We develop a constraint-based model for acceptable ride matches which incorporates route plans and time windows. Through data analytics on a history of advertised schedules and agreed shared trips, we infer parameters for this model that account for 90% of agreed trips. By applying the inferred model to the advertised schedules, we demonstrate that there is an imbalance between riders and passengers. We assess the potential benefits of persuading existing drivers to switch to becoming passengers if appropriate matches can be found, by solving the inferred model with and without switching. We demonstrate that flexible participation has the potential to reduce the number of unmatched participants by up to 80%

Model formulations for pickup and delivery problems in designated driver services

Designated driver services use company vehicles to deliver drivers to customers. The drivers then drive the customers from their origins to their destinations in the customers’ own cars; at the destinations, the drivers are picked up by a company vehicle. We typically see teams of drivers assigned to company vehicles serving customers. However, when the drivers may be dropped off by one vehicle and picked up by another, a challenging pick-up and delivery problem arises. In this paper, we study the structural properties of the designated driver problem focusing on the synchronization between company vehicles and drivers. We present a two-index formulations to generate optimal, least-cost routes using a general-purpose solver. We benchmark the two-index formulations against a 3-index formulation and a path enumeration strategy. Based on a set of experiments, we find that the two-index formulation performs well, both in terms of quality and solution time, especially on the formulations with more flexibility in the pairing of drivers to company vehicles. Our computational experiments show that up to 75% cost savings are possible from using a flexible operating strategy as compared to a strategy in which drivers and company vehicles stay together throughout a shift

Model formulations for pickup and delivery problems in designated driver services

Designated driver services use company vehicles to deliver drivers to customers. The drivers then drive the customers from their origins to their destinations in the customers’ own cars; at the destinations, the drivers are picked up by a company vehicle. We typically see teams of drivers assigned to company vehicles serving customers. However, when the drivers may be dropped off by one vehicle and picked up by another, a challenging pick-up and delivery problem arises. In this paper, we study the structural properties of the designated driver problem focusing on the synchronization between company vehicles and drivers. We present a two-index formulations to generate optimal, least-cost routes using a general-purpose solver. We benchmark the two-index formulations against a 3-index formulation and a path enumeration strategy. Based on a set of experiments, we find that the two-index formulation performs well, both in terms of quality and solution time, especially on the formulations with more flexibility in the pairing of drivers to company vehicles. Our computational experiments show that up to 75% cost savings are possible from using a flexible operating strategy as compared to a strategy in which drivers and company vehicles stay together throughout a shift