Milena Janjevic, PhD
Research Scientist / Engineer
- Cambridge MA UNITED STATES
Dr. Janjevic's current research focuses on the design of supply chain networks.
Media
Social
Biography
Dr. Janjevic received her Ph.D. and Masters in Engineering with specializations in Logistics at Université libre de Bruxelles in Belgium. During her Ph.D., she was a Visiting Scholar at the Center of Excellence for Sustainable Urban Freight Systems at Rensselaer Polytechnic Institute in New York. Her doctoral studies focused on the optimal design of urban logistics systems based on multi-tier distribution networks, electric vehicles, and policy measures. Dr. Janjevic's previous professional work includes working with McKinsey & Company in Belgium and France on various projects in the telecommunication, insurance, and retail sectors.
Dr. Janjevic recently published academic papers in the European Journal of Operational Research, Transportation Research Part A, Transportation Research Part D, Transportation Research Part E, and Environmental Science & Policy. She is also a lecturer at the Massachusetts Institute of Technology (United States).
Research Focus
Supply Chain Strategy & Network Architecture
Designing the structural configuration and competitive positioning of supply networks.
Intelligent & Autonomous Supply Chains
AI-driven, data-centric, and increasingly autonomous decision systems for supply chain planning and execution.
Critical Systems & Supply Network Resilience
Ensuring continuity, preparedness, and mission assurance under disruption and geopolitical volatility.
Areas of Expertise
Education
Université libre de Bruxelles
PhD
Transport and Logistics Management
2016
Université libre de Bruxelles
MS
Electromechanical Engineering
2009
Université libre de Bruxelles
BS
Engineering
2007
Languages
- English
- French
- Serbian
Media Appearances
6 ways to reduce last-mile delivery costs
TechTarget
2025-07-10
Supply chain leaders should use supply chain management technology to better understand their network, the types of vehicles best suited for delivery in each area and optimal locations for fulfillment centers, said Milena Janjevic, a research scientist at the MIT Center for Transportation & Logistics.
Speaking Engagements/Featured Conversations
Analytics Driven Supply Chain: Design Key Challenges and Opportunities
Milena Janjevic, a research scientist at the Megacity Logistics Lab at MIT’s Center for Transportation and Logistics, will discuss new approaches and models for supply chain design, as well as the tools that enable them. Watch full presentation: https://www.youtube.com/watch?v=0lOSDwXC5sg
IAPHL Webinar: The last mile strategies for the pharmaceutical sector with Dr. Milena Janjevic.
Dr. Janjevic explores cutting-edge strategies to optimize the last mile in the pharmaceutical sector, addressing how data-driven optimization, simulation models, and multidisciplinary approaches can revolutionize supply chain efficiency. With extensive experience in urban logistics systems and collaborations across industries, Dr. Janjevic brings a wealth of knowledge to this critical topic. Watch the full webinar: https://www.youtube.com/watch?v=SKL4Xpq-5eE
Research Papers
A strategic assessment of first-mile post-consumer textile collection strategies
Cleaner Logistics and Supply ChainRafael Arevalo-Ascanio, Annelies De Meyer, Milena Janjevic, Roel Gevaers, Ruben Guisson, Wouter Dewulf
2025-10-10
The study of traditional supply chains has evolved to incorporate reverse logistics into closed-loop supply chains in the pursuit of sustainability. The recovery of used materials at the consumer level involves first-mile logistics operations for collection and transport to sorting and recycling centres. In the case of post-consumer materials, multiple collection strategies with distinct challenges may be implemented, alongside the critical role of consumer participation, an aspect that has not been sufficiently modelled. This study proposes an assessment of three collection strategies for post-consumer textiles: collection via outdoor containers, door-to-door collection, and collection through local stores. In some of these strategies, consumer mobilisation to drop off textiles is a key component.
Regress, reverse, recycle: Contextual stochastic optimization in waste policy and logistics network design
MIT Center for Transportation & Logistics Research Paper SeriesAustin Saragih, Milena Janjevic, Yossi Sheffi, Jan C Fransoo
2025-04-22
Effective policies and reverse logistics networks for Municipal Solid Waste (MSW) recycling are crucial for advancing the circular economy. Current approaches to MSW recycling often decouple reverse logistics from endogenous recycling policies and separate waste collection routing from network design, failing to capture critical interdependencies. We address these limitations by incorporating endogenous recycling policy estimation and collection routing into Reverse Logistics Network Design (RLND). Our methodology uses Post Double Selection with Rigorous Lasso (PDS RLasso) to regress recycling rates against municipal policies and characteristics, then optimizes the reverse logistics network using Empirical Residuals-based Sample Average Approximation (ER-SAA). This approach enables the transformation of endogenous policies into exogenous ones for optimization.
Empirical study on consumer’s acceptance of delivery robots in France
International Journal of Logistics Research and ApplicationsOuail Oulmakki, Jerome Verny, Milena Janjevic, Marwa Khalfalli
2024-11-01
The growth of e-commerce has led to an increase in delivery options, and various innovations, such as autonomous delivery robots (ADRs) are being developed to meet the important challenges of the last mile. Currently, in the testing state, consumer acceptance remains relatively unknown. This study aims to identify the factors that affect the level of consumer acceptance of autonomous robotic delivery in urban areas using consumers’ current knowledge of this technology. To answer this question, the factors that negatively or positively influence user acceptance are first determined, and then the validity of the relationships between the factors and user acceptance are tested empirically. The results show that participants of this study are neutral to ADRs, which is reasonable for newly developed technology.
Courses
SCM.275 Advanced Supply Chain Systems Planning and Network Design
A graduate-level course focused on the strategic design and planning of supply chain networks. The course covers optimization models for transportation, facility location, inventory, transshipment, and network configuration, with an emphasis on using data, mathematical optimization, and computational tools to support complex supply chain decisions.