17 research outputs found
Dynamic demand management and online tour planning for same-day delivery
For providers to stay competitive in a context of continued growth in e-retail sales and increasing customer expectations, same-day delivery options have become very important. Typically, with same-day delivery, customers purchase online and expect to receive their ordered goods within a narrow delivery time span. Providers thus experience substantial operational challenges to run profitable tours and generate sufficiently high contribution margins to cover overhead costs. We address these challenges by combining a demand-management approach with an online tour-planning approach for same-day delivery. More precisely, in order to reserve capacity for high-value customer orders and to guide customer choices toward efficient delivery operations, we propose a demand-management approach that explicitly optimizes the combination of delivery spans and prices which are presented to each incoming customer request. The approach includes an anticipatory sample-scenario based value approximation, which incorporates a direct online tour-planning heuristic. It does not require extensive offline learning and is scalable to realistically sized instances with multiple vehicles. In a comprehensive computational study, we show that our anticipatory approach can improve the contribution margin by up to 50% compared to a myopic benchmark approach. We also show that solving an explicit pricing optimization problem is a beneficial component of our approach. More precisely, it outperforms both a pure availability control and a simple pricing rule based on opportunity costs. The latter idea is one used in other approaches for related dynamic pricing problems dealt with in the literature
A review of revenue management : recent generalizations and advances in industry applications
Originating from passenger air transport, revenue management has evolved into a general and indispensable methodological framework over the last decades, comprising techniques to manage demand actively and to further improve companies’ profits in many different industries. This article is the second and final part of a paper series surveying the scientific developments and achievements in revenue management over the past 15 years. The first part focused on the general methodological advances regarding choice-based theory and methods of availability control over time. In this second part, we discuss some of the most important generalizations of the standard revenue management setting: product innovations (opaque products and flexible products), upgrading, overbooking, personalization, and risk-aversion. Furthermore, to demonstrate the broad use of revenue management, we survey important industry applications beyond passenger air transportation that have received scientific attention over the years, covering air cargo, hotel, car rental, attended home delivery, and manufacturing. We work out the specific revenue management-related challenges of each industry and portray the key contributions from the literature. We conclude the paper with some directions for future research
Dynamic Route Planning for Last-Mile Delivery
There has never been a time with more demand than now for e-retailing and as a consequence last-mile services. The growth in demand is also bringing significant challenges. With the abundance of options, customers are ever more demanding and expecting more control. With the existing strategies, matching customers' foregoing expectations causes significant economic burdens and ecological disturbances. As a result, e-retailers need to define efficient routing strategies for their last-mile services. This thesis is motivated by identifying efficient routing strategies, in terms of environmental impacts, service time and cost, for last-mile delivery services. We investigate different routing strategies for the last-mile delivery problems, with a focus on same-day services. The corresponding problem is known as the last-mile same-day delivery problem and is dynamic due to the nature of service requests.
In the first part, we investigate vehicle and drone integrated delivery systems. We consider an alternative way to integrate drones into conventional vehicle delivery systems, such that drones resupply vehicles with the future orders of customers while vehicles deliver available orders to customers. We evaluate the impact of the drone resupply system based on a case of the problem in which a single vehicle and a single drone are dedicated to the service area. We introduce a mixed-integer programming model for the delivery problem with known requests. For the dynamic problem in which the requests reveal dynamically throughout the horizon, we propose a periodic reoptimization algorithm as a solution approach. We compare the performance of the drone resupply system to the conventional vehicle only delivery systems over several practical instances that differ in terms of customer preferences and system settings. Through computational experiments, we showed that the drone resupply system outperforms the conventional system with respect to operational time, cost and carbon emissions levels.
In the second part of the thesis, we evaluate the impact of outsourcing strategy in a multi-period delivery problem. Given the relevance of the problem in practice, we suggest that exploitable stochastic information might be gathered for the dynamically revealed information. To the best of our knowledge, we are the first to introduce outsourcing in the literature of dynamic multi-period vehicle routing problems with probabilistic information. We model the corresponding problem as a Markov decision process. We propose a multi-stage programming model and a progressive hedging algorithm to solve the decision problems. We evaluate several planning strategies to evaluate the impact of postponement and outsourcing decisions. Based on the computational experiments, we determined the best delivery strategy in terms of cost over different practical settings
Reports to the President
A compilation of annual reports for the 1999-2000 academic year, including a report from the President of the Massachusetts Institute of Technology, as well as reports from the academic and administrative units of the Institute. The reports outline the year's goals, accomplishments, honors and awards, and future plans
The drivers of Corporate Social Responsibility in the supply chain. A case study.
Purpose: The paper studies the way in which a SME integrates CSR into its corporate strategy, the practices it puts in place and
how its CSR strategies reflect on its suppliers and customers relations.
Methodology/Research limitations: A qualitative case study methodology is used. The use of a single case study limits the
generalizing capacity of these findings.
Findings: The entrepreneur’s ethical beliefs and value system play a fundamental role in shaping sustainable corporate strategy.
Furthermore, the type of competitive strategy selected based on innovation, quality and responsibility clearly emerges both in
terms of well defined management procedures and supply chain relations as a whole aimed at involving partners in the process of
sustainable innovation.
Originality/value: The paper presents a SME that has devised an original innovative business model. The study pivots on the
issues of innovation and eco-sustainability in a context of drivers for CRS and business ethics. These values are considered
fundamental at International level; the United Nations has declared 2011 the “International Year of Forestry”