Dr. Matthias Winkenbach

Research Scientist
Director, MIT Megacity Logistics Lab

Primary DLC

Center for Transportation and Logistics

MIT Room: E40-247B

Areas of Interest and Expertise

Urban Logistics
Last-Mile Logistics
Logistics in Emerging Markets
Megacities
Distribution Network Design
Urban Freight Infrastructure
Urban Logistics Data Analytics
Distribution to Nanostores
Data Visualization
Simulation
Optimization

Research Summary

While urban transportation involves the movement of both freight and passengers in urban areas, the term city logistics is explicitly limited to the domain of urban freight transportation (Bektas et al., 2015). City logistics concepts aim at increasing the efficiency and decreasing the negative environmental, social and economic externalities of urban freight transportation through consolidation and tighter coordination of shipments within an integrated logistics system (see, e.g., Taniguchi, 2014).

The design of multi-tier distribution networks for urban last mile delivery is the centerpiece of Dr. Winkenbach's research (see, e.g., Winkenbach et al., 2016). Moreover, his research addresses issues of infrastructure and policy design for urban freight transportation and delivery, and applications of data analytics, algorithms, and technology innovation in urban transportation.

(1) Multi-Tier Last-Mile Distribution Networks:
Urban Logistics Systems consist of four major elements that are in the focus of Dr. Winkenbach's research:
i) demand patterns within the urban area, determining the traffic flows within the network,
ii) the points of delivery and/or pick-up, their type and position within the urban area,
iii) the facilities used within the network, their number, type/function and position within the urban area, and
iv) the modes and vehicle technologies available for use within different parts of the network.
Relevant methodologies to address research questions in this building block comprise:
- Mixed integer programming
- Continuous approximation
- Stochastic optimization
- Optimization heuristics
- Micro- and macro-simulation

(2) Urban Freight Infrastructure and Policy Design:
The optimal design of urban distribution networks is strongly influenced by the local policy framework. This policy framework consists of the following key elements:
i) regulation,
ii) provision of infrastructure, and
iii) incentive systems.
Relevant methodologies to address research questions in this building block comprise:
- Statistical analysis of socio-economic, infrastructural, and operational data; in particular cluster analysis
- Data visualization
- Case studies
- Practitioner interviews
- Micro- and macro-simulation

(3) Logistics Data Analytics and Technology:
With mobile computing, sensing and communication technologies progressively finding their way into everyday life and the work environment through commonly affordable mobile devices, the following technology trends are becoming increasingly relevant for urban last-mile distribution:
i) low-cost sensor technology (cf., Richter and Poenicke, 2013)
ii) big data and learning (cf., Jeske et al., 2013, Bubner et al., 2014)
Besides these developments on the data and analytics side, we can also observe continuous technological advances with respect to the facility infrastructure, equipment, and fleet that make up distribution networks for last-mile delivery:
iii) new vehicle types and engine technologies (cf., Kleindorfer et al., 2012, Neboian and Spinler, 2015)
iv) process automation and autonomous technologies (cf., Niezgoda and Chung, 2014, Bubner et al., 2014)
The above mentioned technology trends are complementary and may have overlaps with
v) advances in augmented reality applications (cf., Glockner et al., 2014), and
vi) the Internet of Things concept (cf., Macaulay et al., 2015).
Relevant methodologies to address research questions in this building block comprise:
- Statistical analysis of structured and unstructured data
- Machine learning
- Micro- and macro-simulation
- Optimization
- Field studies
- Data visualization

Recent Work

  • Video

    10.28.20-Mobility-Matthias-Winkenbach

    October 28, 2020Conference Video Duration: 59:21
    Matthias Winkenbach
    Director, MIT Megacity Logistics Lab
    Research Scientist
    MIT Center for Transportation and Logistics

    Mattias Winkenbach

    January 9, 2018MIT Faculty Feature Duration: 24:52

    MIT

    Matthias Winkenbach - 2017 Management

    October 4, 2017Conference Video Duration: 34:25

    Managing the Last Mile: Density, Data, and Technology

    There are three major complexities facing those who manage last-mile distribution: increasing density in megacities, increasing fragmentation of urban demand, and ever-increasing customer expectations. How can technology and data improve last-mile logistics? What unique challenges do managers face? How can you understand shifting consumer expectations and the evolution of omni-channel retail and delivery in city environments? Join Matthias Winkenbach to explore how companies can reach customers on their own terms, where they live, work, shop, or play, anywhere on the globe.

    2017 MIT Innovations in Management Conference

    Matthias Winkenbach - 2016-Consumer-Dynamics-Conf

    December 14, 2016Conference Video Duration: 34:40

    Megacities and the Last-Mile Problem

    Rapid urbanization and increasing population density in megacities poses unique challenges for last-mile distribution in many of the world’s largest emerging markets. Meeting these challenges requires understanding shifting consumer expectations and the evolution of omni-channel retail and delivery in city environments. These insights can help companies leverage logistics big data analytics for last-mile network design and planning to reach customers on their own terms, where they live, work, shop, or play, anywhere on the globe.

    2016 MIT Consumer Dynamics Conference