scholarly journals Fleet sizing and allocation for on-demand last-mile transportation systems

2021 ◽  
Vol 132 ◽  
pp. 103387
Author(s):  
Karmel S. Shehadeh ◽  
Hai Wang ◽  
Peter Zhang
Keyword(s):  
Transportation Systems ◽  
Fleet Sizing ◽  
On Demand ◽  
Last Mile

On-Demand Public Transit: A Markovian Continuous Approximation Model

2021 ◽  
Author(s):  
Daniel F. Silva ◽  
Alexander Vinel ◽  
Bekircan Kirkici
Keyword(s):  
System Performance ◽  
Performance Metrics ◽  
Public Transit ◽  
Continuous Approximation ◽  
Efficient Operation ◽  
Fleet Sizing ◽  
On Demand ◽  
Single Vehicle ◽  
Transit Agencies ◽  
Using Data

With recent advances in mobile technology, public transit agencies around the world have started actively experimenting with new transportation modes, many of which can be characterized as on-demand public transit. Design and efficient operation of such systems can be particularly challenging, because they often need to carefully balance demand volume with resource availability. We propose a family of models for on-demand public transit that combine a continuous approximation methodology with a Markov process. Our goal is to develop a tractable method to evaluate and predict system performance, specifically focusing on obtaining the probability distribution of performance metrics. This information can then be used in capital planning, such as fleet sizing, contracting, and driver scheduling, among other things. We present the analytical solution for a stylized single-vehicle model of first-mile operation. Then, we describe several extensions to the base model, including two approaches for the multivehicle case. We use computational experiments to illustrate the effects of the inputs on the performance metrics and to compare different modes of transit. Finally, we include a case study, using data collected from a real-world pilot on-demand public transit project in a major U.S. metropolitan area, to showcase how the proposed model can be used to predict system performance and support decision making.

scholarly journals Analysis and Control of Autonomous Mobility-on-Demand Systems

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Gioele Zardini ◽  
Nicolas Lanzetti ◽  
Marco Pavone ◽  
Emilio Frazzoli
Keyword(s):  
Performance Metrics ◽  
Transportation Systems ◽  
Demand Systems ◽  
Annual Review ◽  
Publication Date ◽  
Systematic Analysis ◽  
On Demand ◽  
Trade Offs ◽  
Autonomous Mobility ◽  
And Control

Challenged by urbanization and increasing travel needs, existing transportation systems need new mobility paradigms. In this article, we present the emerging concept of autonomous mobility-on-demand, whereby centrally orchestrated fleets of autonomous vehicles provide mobility service to customers. We provide a comprehensive review of methods and tools to model and solve problems related to autonomous mobility-on-demand systems. Specifically, we first identify problem settings for their analysis and control, from both operational and planning perspectives. We then review modeling aspects, including transportation networks, transportation demand, congestion, operational constraints, and interactions with existing infrastructure. Thereafter, we provide a systematic analysis of existing solution methods and performance metrics, highlighting trends and trade-offs. Finally, we present various directions for further research. Expected final online publication date for the Annual Review of Control, Robotics, and Autonomous Systems, Volume 5 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

scholarly journals A Discrete Simulation-Based Optimization Algorithm for the Design of Highly Responsive Last-Mile Distribution Networks

2021 ◽  
Author(s):  
André Snoeck ◽  
Matthias Winkenbach
Keyword(s):  
Network Design ◽  
Distribution Network ◽  
Distribution Networks ◽  
Optimization Techniques ◽  
On Demand ◽  
Distribution Network Design ◽  
Last Mile ◽  
Simulation Based ◽  
Simulation Based Optimization ◽  
Congestion Effects

Online and omnichannel retailers are proposing increasingly tight delivery deadlines, moving toward instant on-demand delivery. To operate last-mile distribution systems with such tight delivery deadlines efficiently, defining the right strategic distribution network design is of paramount importance. However, this problem exceeds the complexity of the strategic design of traditional last-mile distribution networks for two main reasons: (1) the reduced time available for order handling and delivery and (2) the absence of a delivery cut-off time that clearly separates order collection and delivery periods. This renders state-of-the-art last-mile distribution network design models inappropriate, as they assume periodic order fulfillment based on a delivery cutoff. In this study, we propose a metamodel simulation-based optimization (SO) approach to strategically design last-mile distribution networks with tight delivery deadlines. Our methodology integrates an in-depth simulator with traditional optimization techniques by extending a traditional black-box SO algorithm with an analytical model that captures the underlying structure of the decision problem. Based on a numerical study inspired by the efforts of a global fashion company to introduce on-demand distribution with tight delivery deadlines in Manhattan, we show that our approach outperforms contemporary SO approaches as well as deterministic and stochastic programming methods. In particular, our method systematically yields network designs with superior expected cost performance. Furthermore, it converges to good solutions with a lower computational budget and is more consistent in finding high-quality solutions. We show how congestion effects in the processing of orders at facilities negatively impact the network performance through late delivery of orders and reduced potential for consolidation. In addition, we show that the sensitivity of the optimal network design to congestion effects in order processing at the facilities increases as delivery deadlines become increasingly tight.

scholarly journals Travellers’ preferences towards existing and emerging means of first/last mile transport: a case study for the Almere centrum railway station in the Netherlands

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Bas Stam ◽  
Niels van Oort ◽  
Hilke J. van Strijp-Harms ◽  
Stefan C. van der Spek ◽  
Serge P. Hoogendoorn
Keyword(s):  
Mode Choice ◽  
Main Stage ◽  
Factors Affecting ◽  
On Demand ◽  
Policy Interventions ◽  
Technology Advancement ◽  
Complex Process ◽  
Last Mile ◽  
Policy Objectives ◽  
Demographic Shifts

AbstractFirst/last mile transport is essential for transit but is often found to be the weakest link in a trip. Moreover, as a result of multiple developments (e.g. demographic shifts, urbanization, climate change, technology advancement) first/last mile transport will likely change rapidly. The literature review of this study shows six different categories of factors affecting first/last mile mode choice: (1) traveller, (2) psychological, (3) first/last mile trip, (4) first/last mile modes, (5) built environment, and (6) main stage. We used this framework to understand and predict the complex process of mode choice, specifically given the emerge of new modes. The performed mode choice experiment shows varying results regarding the preferences of travellers for existing and new means of first/last mile transport. Four future scenarios (varying in level of sharing and flexibility of rides) are investigated. Traditional means of transport such as private vehicles and traditional ride services remain preferred over shared vehicles and on-demand ride services. For instance, 21% of the travellers chooses a private but no shared vehicle, and 12% chooses a traditional but no on-demand ride service. On the other hand, 21% of the travellers prefer a shared vehicle and 23% prefer an on-demand ride service whenever these vehicles/services are available. These results illustrate that when mode choice factors are absent and there are no restrictions taken into account (for example the possession of a car and driving license when choosing car), the actual chosen means of transport in the current situation differs from the preferred means of transport in the future. The results also show potential for new, emerging, means of first/last mile transport. According to the ‘preferred situation’ by travellers, transit nodes and first/last mile systems require a different design regarding first/last mile facilities, dependent on the scenario(s) that will develop. The challenge for decision makers and planners is to steer mode choice decisions in the direction according to their policy objectives, where our insights support the corresponding design choices and policy interventions.

scholarly journals Planning the use of helicopters in the last mile distribution process in catastrophes

2021 ◽  
Vol 28 (4) ◽  
Author(s):  
Iran Rosa Xavier ◽  
Renata Albergaria de Mello Bandeira ◽  
Leandro de Oliveira Silva ◽  
Adriano de Paula Fontainhas Bandeira ◽  
Vânia Barcellos Gouvêa Campos ◽  
...  
Keyword(s):  
Disaster Response ◽  
Large Scale ◽  
Transportation Systems ◽  
Air Transport ◽  
Earthquake Response ◽  
Multiple Products ◽  
Last Mile ◽  
Hypothetical Scenario ◽  
Distribution Process ◽  
Key Steps

Abstract: The shortage of funding, the challenging assessment of aid needs, and the lack of transportation systems for the rescue and care of victims represent major constraints to disaster response operations. In order to improve logistical performance in these conditions, including remote and large areas, this paper proposes a formal mathematical model to assist air transport planning, using helicopters, for large-scale disasters, considering multiple deposit systems, multiples vehicles and multiple products, implemented in AIMMS to evaluate its performance. To achieve the objectives, a literature review is conducted to understand the ways in which helicopters are used in aid operations and to identify key steps in decision making and modeling processes. In the end, a hypothetical scenario is created with similar characteristics from the records of earthquake response operations that hit Haiti in 2010 for consolidation and validation of the procedure.

scholarly journals On-demand food delivery: investigating the economic performances

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Arianna Seghezzi ◽  
Riccardo Mangiaracina
Keyword(s):  
Purchase Intention ◽  
Design Methodology ◽  
Food Delivery ◽  
Sensitivity Analyses ◽  
Base Case ◽  
Content Type ◽  
On Demand ◽  
Last Mile ◽  
Potential Impact ◽  
Positive Results

PurposeThis paper focusses on on-demand food delivery (ODFD), i.e. the delivery of freshly prepared meals to customers' homes, enabled by the use of online platforms. In ODFD, a key process is represented by last-mile deliveries (LMDs): they directly affect customers (the delivery price influences their purchase intention), riders (the compensation drives their willingness to perform deliveries) and platforms (deliveries are very expensive). In this context, this work aims to investigate the economic performances of ODFD LMDs.Design/methodology/approachThis study adopts a multi-method threefold process. First, it develops a model that – after the generation of customers' demand and the assignment of deliveries to available riders – identifies incomes and costs faced by an ODFD operator. Second, the model is applied to a base case in Milan (Italy). Third, sensitivity analyses are performed (on daily demand and riders' salary).FindingsThe analyses allow – besides the identification of significant values associated to ODFD profitability – to draw general insights about delivery price (e.g. free delivery is not economically sustainable), daily demand (e.g. greater demand values do not only improve positive results but also worsen negative ones) and fixed/variable wage mix (e.g. increasing the variable wage enhances the profitability for platforms).Originality/valueOn the academic side, this word enhances extant literature about ODFD, proposing a model – with multidisciplinary implications – to strategically investigate profitability conditions of LMDs. On the managerial side, it provides support for (logistics/marketing) ODFD practitioners since it allows to evaluate the potential impact of significant decisions on profitability.

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