A decomposition-based approach for large-scale pickup and delivery problems

With the advent of self-driving cars, experts envision autonomous mobility-on-demand services in the near future to cope with overloaded transportation systems in cities worldwide. Efficient operations are imperative to unlock such a system's maximum improvement potential. Existing approaches either consider a narrow planning horizon or ignore essential characteristics of the underlying problem. In this paper, we develop an algorithmic framework that allows the study of very large-scale pickup and delivery routing problems with more than 20 thousand requests, which arise in the context of integrated request pooling and vehicle-to-request dispatching. We conduct a computational study and present comparative results showing the characteristics of the developed approaches. Furthermore, we apply our algorithm to related benchmark instances from the literature to show the efficacy. Finally, we solve very large-scale instances and derive insights on upper-bound improvements regarding fleet sizing and customer delay acceptance from a practical perspective

Strategic Workforce Planning in Crowdsourced Delivery with Hybrid Driver Fleets

Nowadays, logistics service providers (LSPs) increasingly consider using a crowdsourced workforce on the last mile to fulfill customers' expectations regarding same-day or on-demand delivery at reduced costs. The crowdsourced workforce's availability is, however, uncertain. Therefore, LSPs often hire additional fixed employees to perform deliveries when the availability of crowdsourced drivers is low. In this context, the reliability versus flexibility trade-off which LSPs face over a longer period, e.g., a year, remains unstudied. Against this background, we jointly study a workforce planning problem that considers fixed drivers (FDs) and the temporal development of the crowdsourced driver (CD) fleet over a long-term time horizon. We consider two types of CDs, gigworkers (GWs) and occasional drivers (ODs). While GWs are not sensitive to the request's destination and typically exhibit high availability, ODs only serve requests whose origin and destination coincide with their own private route's origin and destination. Moreover, to account for time horizon-specific dynamics, we consider stochastic turnover for both FDs and CDs as well as stochastic CD fleet growth. We formulate the resulting workforce planning problem as a Markov decision process (MDP) whose reward function reflects total costs, i.e., wages and operational costs arising from serving demand with FDs and CDs, and solve it via approximate dynamic programming (ADP). Applying our approach to an environment based on real-world demand data from GrubHub, we find that in fleets consisting of FDs and CDs, ADP-based hiring policies can outperform myopic hiring policies by up to 19% in total costs. In the studied setting, we observed that GWs reduce the LSP's total costs more than ODs. When we account for CDs' increased resignation probability when not being matched with enough requests, the amount of required FDs increases.Comment: 45 pages, 21 figure

Staggered Routing in Autonomous Mobility-on-Demand Systems

In autonomous mobility-on-demand systems, effectively managing vehicle flows to mitigate induced congestion and ensure efficient operations is imperative for system performance and positive customer experience. Against this background, we study the potential of staggered routing, i.e., purposely delaying trip departures from a system perspective, in order to reduce congestion and ensure efficient operations while still meeting customer time windows. We formalize the underlying planning problem and show how to efficiently model it as a mixed integer linear program. Moreover, we present a matheuristic that allows us to efficiently solve large-scale real-world instances both in an offline full-information setting and its online rolling horizon counterpart. We conduct a numerical study for Manhattan, New York City, focusing on low- and highly-congested scenarios. Our results show that in low-congestion scenarios, staggering trip departures allows mitigating, on average, 94% of the induced congestion in a full information setting. In a rolling horizon setting, our algorithm allows us to reduce 90% of the induced congestion. In high-congestion scenarios, we observe an average reduction of 66% as the full information bound and an average reduction of 56% in our online setting. Surprisingly, we show that these reductions can be reached by shifting trip departures by a maximum of six minutes in both the low and high-congestion scenarios.Comment: 32 pages, 10 figure

Metaheuristics for solving a multimodal home-healthcare scheduling problem

Abstract We present a general framework for solving a real-world multimodal home-healthcare scheduling (MHS) problem from a major Austrian home-healthcare provider. The goal of MHS is to assign home-care staff to customers and determine efficient multimodal tours while considering staff and customer satisfaction. Our approach is designed to be as problem-independent as possible, such that the resulting methods can be easily adapted to MHS setups of other home-healthcare providers. We chose a two-stage approach: in the first stage, we generate initial solutions either via constraint programming techniques or by a random procedure. During the second stage, the initial solutions are (iteratively) improved by applying one of four metaheuristics: variable neighborhood search, a memetic algorithm, scatter search and a simulated annealing hyper-heuristic. An extensive computational comparison shows that the approach is capable of solving real-world instances in reasonable time and produces valid solutions within only a few seconds

An investigation of heuristic decomposition to tackle workforce scheduling and routing with time-dependent activities constraints

This paper presents an investigation into the application of heuristic decomposition and mixed-integer programming to tackle workforce scheduling and routing problems (WSRP) that involve timedependent activities constraints. These constraints refer to time-wise dependencies between activities. The decomposition method investigated here is called repeated decomposition with con ict repair (RDCR) and it consists of repeatedly applying a phase of problem decomposition and sub-problem solving, followed by a phase dedicated to con ict repair. In order to deal with the time-dependent activities constraints, the problem decomposition puts all activities associated to the same location and their dependent activities in the same sub-problem. This is to guarantee the satisfaction of time-dependent activities constraints as each sub-problem is solved exactly with an exact solver. Once the assignments are made, the time windows of dependent activities are fixed even if those activities are subject to the repair phase. The paper presents an experimental study to assess the performance of the decomposition method when compared to a tailored greedy heuristic. Results show that the proposed RDCR is an effective approach to harness the power of mixed integer programming solvers to tackle the diffcult and highly constrained WSRP in practical computational time. Also, an analysis is conducted in order to understand how the performance of the different solution methods (the decomposition, the tailored heuristic and the MIP solver) is accected by the size of the problem instances and other features of the problem. The paper concludes by making some recommendations on the type of method that could be more suitable for different problem sizes

Inventing a herbal tradition: The complex roots of the current popularity of Epilobium angustifolium in Eastern Europe

Ethnopharmacological relevance: Currently various scientific and popular sources provide a wide spectrum of ethnopharmacological information on many plants, yet the sources of that information, as well as the information itself, are often not clear, potentially resulting in the erroneous use of plants among lay people or even in official medicine. Our field studies in seven countries on the Eastern edge of Europe have revealed an unusual increase in the medicinal use of Epilobium angustifolium L., especially in Estonia, where the majority of uses were specifically related to “men's problems”. The aim of the current work is: to understand the recent and sudden increase in the interest in the use of E. angustifolium in Estonia; to evaluate the extent of documented traditional use of E. angustifolium among sources of knowledge considered traditional; to track different sources describing (or attributed as describing) the benefits of E. angustifolium; and to detect direct and indirect influences of the written sources on the currently documented local uses of E. angustifolium on the Eastern edge of Europe. Materials and methods: In this study we used a variety of methods: semi-structured interviews with 599 people in 7 countries, historical data analysis and historical ethnopharmacological source analysis. We researched historical and archival sources, and academic and popular literature published on the medicinal use of E. angustifolium in the regions of our field sites as well as internationally, paying close attention to the literature that might have directly or indirectly contributed to the popularity of E. angustifolium at different times in history. Results: Our results show that the sudden and recent popularity in the medical use of E. angustifolium in Estonia has been caused by local popular authors with academic medical backgrounds, relying simultaneously on “western” and Russian sources. While Russian sources have propagated (partially unpublished) results from the 1930s, “western” sources are scientific insights derived from the popularization of other Epilobium species by Austrian herbalist Maria Treben. The information Treben disseminated could have been originated from a previous peak in popularity of E. angustifolium in USA in the second half of the 19th century, caused in turn by misinterpretation of ancient herbals. The traditional uses of E. angustifolium were related to wounds and skin diseases, fever, pain (headache, sore throat, childbirth), and abdominal-related problems (constipation, stomach ache) and intestinal bleeding. Few more uses were based on the similarity principle. The main theme, however, is the fragmentation of use and its lack of consistency apart from wounds and skin diseases. Conclusions: Historical ethnobotanical investigations could help to avoid creating repeating waves of popularity of plants that have already been tried for certain diseases and later abandoned as not fully effective. There is, of course, a chance that E. angustifolium could also finally be proven to be clinically safe and cost-effective for treating benign prostatic hyperplasia, but this has not yet happened despite recent intensive research. Documented traditional use would suggest investigating the dermatological, intestinal anti-hemorrhagic and pain inhibiting properties of this plant, if any