Savelsbergh, M.W.P.

Revenue management opportunities for Internet retailers (Article)

2013-03-01T00:00:00Z

In this article, 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. 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.

Optimization for dynamic ride-sharing: A review (Article)

2012-12-01T00:00:00Z

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 (Article)

2011-08-01T00:00:00Z

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.

Time Slot Management in Attended Home Delivery (Article)

2011-08-01T00:00:00Z

Dynamic ride-sharing: A simulation study in metro Atlanta (Article)

2011-07-21T00:00:00Z

Smartphone technology enables dynamic ride-sharing systems that bring together people with similar itineraries and time schedules to share rides on short-notice. This paper considers the problem of matching drivers and riders in this dynamic setting. We develop optimization-based approaches that aim at minimizing the total system-wide vehicle miles incurred by system users, and their individual travel costs. To assess the merits of our methods we present a simulation study based on 2008 travel demand data from metropolitan Atlanta. The simulation results indicate that the use of sophisticated optimization methods instead of simple greedy matching rules substantially improve the performance of ride-sharing systems. Furthermore, even with relatively low participation rates, it appears that sustainable populations of dynamic ride-sharing participants may be possible even in relatively sprawling urban areas with many employment centers.

Dynamic Ride-Sharing: a Simulation Study in Metro Atlanta (Article)

2011-01-01T00:00:00Z

The Value of Optimization in Dynamic Ride-Sharing: a Simulation Study in Metro Atlanta (Research Paper)

2010-08-17T00:00:00Z

Smartphone technology enables dynamic ride-sharing systems that bring together people with similar itineraries and time schedules to share rides on short-notice. This paper considers the problem of matching drivers and riders in this dynamic setting. We develop optimization-based approaches that aim at minimizing the total system-wide vehicle miles and individual travel costs. To assess the merits of our methods we present a simulation study based on 2008 travel demand data from metropolitan Atlanta. The simulation results indicate that the use of sophisticated optimization methods instead of simple greedy matching rules may substantially improve the performance of ride-sharing systems. Furthermore, even with relatively low participation rates, it appears that sustainable populations of dynamic ride-sharing participants may be possible even in relatively sprawling urban areas with many employment centers.

Sustainable Passenger Transportation: Dynamic Ride-Sharing (Research Paper)

2010-02-25T00:00:00Z

Ride-share systems, which aim to bring together travelers with similar itineraries and time schedules, 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 ride-share system. We formally define dynamic ride-sharing and outline the optimization challenges that arise when developing technology to support ride-sharing. We hope that this paper will encourage more research by the transportation science and logistics community in this exciting, emerging area of public transportation.

Demand Management Opportunities in E-fulfillment: What Internet Retailers Can Learn from Revenue Management (Research Paper)

2008-04-25T00:00:00Z

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.

Time Slot Management in Attended Home Delivery (Research Paper)

2008-04-16T00:00:00Z

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.

Minimum vehicle fleet size under time window constraints at a container terminal (Article)

2005-05-01T00:00:00Z

Products can be transported in containers from one port to another. At a container terminal these containers are transshipped from one mode of transportation to another. Cranes remove containers from a ship and put them at a certain time (i.e., release time) into a buffer area with limited capacity. A vehicle lifts a container from the buffer area before the buffer area is full (i.e., in due time) and transports the container from the buffer area to the storage area. At the storage area the container is placed in another buffer area. The advantage of using these buffer areas is the resultant decoupling of the unloading and transportation processes. We study the case in which each container has a time window [release time, due time] in which the transportation should start. The objective is to minimize the vehicle fleet size such that the transportation of each container starts within its time window. No literature has been found studying this relevant problem. We have developed an integer linear programming model to solve the problem of determining vehicle requirements under time-window constraints. We use simulation to validate the estimates of the vehicle fleet size by the analytical model. We test the ability of the model under various conditions. From these numerical experiments we conclude that the results of the analytical model are close to the results of the simulation model. Furthermore, we conclude that the analytical model performs well in the context of a container terminal.

Local search in physical distribution management (Research Paper)

1992-01-01T00:00:00Z

Physical distribution management presents a variety of decision making problems at three levels of strategic, tactical and operational planning. The importance of effective and efficient distribution management is evident from its associated costs. Physical distribution management at the operational level, which is considered in this paper is responsible for an important fraction of the total distribution costs. Not surprisingly, there is a growing demand for planning systems that produce economical routes. Enormous theoretical as well as practical advances have been made, in the last decade. Some of the resulting vehicle and scheduling models will be discussed in this paper, like vehicle routing problem with time window and the pickup and delivery problem with time window.

Sequential and parallel local search for the time-constrained travelling salesman problem (Research Paper)

1990-01-01T00:00:00Z

Local search has proven to be an effective solution approach for the traveling salesman problem. We consider variants of the TSP in which each city is to be visited within one or more given time windows. The travel times are symmetric and satisfy the triangle inequality; therobjective is to minimize the tour duration. We develop efficient sequential and parallel algorithms for the verification of local optimality of a tour with respect to k-exchanges.

Parallel local search for the time-constrained traveling salesman problem (Research Paper)

1989-01-01T00:00:00Z

In the time-constrained TSP, each city has to be visited within a given time interval. Such `time windows' often occur in practice. When practical vehicle routing problems are solved in an interactive setting, one needs algorithms for the time-constrained TSP that combine a low running time with a high solution quality. Local search seems a natural approach. It is not obvious, however, how local search for the TSP has to be implemented so as to handle time windows efficiently. This is particularly true when parallel computer architectures are available. We consider these questions.