Mohammad Moshref Javadi

Teaching Assistant Professor of Business Administration and Director of Illinois Supply Chain Management Corporate Affiliates Program and Deloitte Scholar

Contact

4024 Business Instructional Facility

515 Gregory Dr

Champaign, IL 61820

217-333-4940

moshref@illinois.edu

Google Scholar

Listings

Educational Background

Ph.D., Industrial Engineering, Purdue University, 2017

Positions Held

Director of Illinois Supply Chain Management Corporate Affiliates Program, Business Administration, University of Illinois at Champaign-Urbana, 2023 to present
Teaching Assistant Professor, Business Administration, University of Illinois at Urbana-Champaign, 2021 to present
Visiting Assistant Professor, D'amore-McKim School of Business, Northeastern University, 2019-2021
Postdoctoral Associate, Center for Transportation and Logistics, Massachusetts Institute of Technology, 2017-2019

Recent Publications

Moshref Javadi, M., & Seshadri, S. (2024). Adjustments to Supply Chains in Response to the COVID-19 Pandemic: A Survey. Switzerland: Springer.
Roytvand Ghiasvand, M., Rahmani, D., & Moshref-Javadi, M. (2024). Data-driven robust optimization for a multi-trip truck-drone routing problem. Expert Systems with Applications, 241 122485.
Moshref Javadi, M., & Seshadri, S., Mohammad Moshref-Javadi and Sridhar Seshadri (Ed.) (2024). Impacts of COVID-19 on Supply Chains - Disruptions, Technologies, and Solutions. Switzerland: Springer.
Ahsen, M., & Moshref Javadi, M. (2024). The Role of Technologies in Supply Chain Efficiency and Resiliency. Switzerland: Springer.
Moshref-Javadi, M., Van Cauwenberghe, K., McCunney, B., & Hemmati, A. (2023). Enabling Same-day Delivery Using a Drone Resupply Model with Transshipment Points. Computational Management Science, 20 (1), 22.
Johannessen, P., Hemmati, A., & Moshref Javadi, M. (2022). Solving a pickup and delivery routing problem for fourth-party logistics providers. International Transactions in Operational Research.

Other Publications

Articles

Bruni, M., Khodaparasti, S., & Moshref Javadi, M. (2022). A logic-based Benders decomposition method for the multi-trip traveling repairman problem with drones. Computers & Operations Research, 145 105845.
Matthias, W., & Moshref Javadi, M. (2022). A new way to classify drone-based logistics models. Supply Chain Management Review.
Moshref Javadi, M., Hemmati, ., & Winkenbach, . (2021). A Comparative Analysis of Synchronized Truck-and-Drone Delivery Models. Computers & Industrial Engineering, 162 107648.
Moshref Javadi, M., & Winkenbach, M. (2021). Applications and Research Avenues for Drone-Based Models in Logistics: A Classification and Review. Expert Systems with Applications, 177 114854.
Moshref Javadi, M., Lee, S., & Winkenbach, M. (2020). Design and Evaluation of a Multi-Trip Delivery Model with Truck and Drones. Transportation Research Part E: Logistics and Transportation Review, 136 101887.
Moshref Javadi, M., Hemmati, A., & Winkenbach, M. (2019). A Truck and Drones Model for Last-mile Delivery: A Mathematical Model and Heuristic Approach. Applied Mathematical Modeling, 80 290-318.
Kitjacharoenchai, P., Ventresca, M., Moshref Javadi, M., Lee, S., Tanchoco, J., & Brunese, P. (2019). Multiple Traveling Salesman Problem with Drones: Mathematical model and heuristic approach. Computers & Industrial Engineering, 129 14-30.
Sabouhi, F., Bozorgi-Amiri, A., Moshref Javadi, M., & Heydari, M. (2018). An integrated routing and scheduling model for evacuation and commodity distribution in large-scale disaster relief operations: A case study. Annals of Operations Research, 283 643-677.
Moshref Javadi, M., & Lee, S. (2016). The Customer-centric, Multi-commodity Vehicle Routing Problem with Split Delivery. Expert Systems with Applications, 56 335-348.
Moshref Javadi, M., & Lee, S. (2016). The Latency Location-Routing Problem. European Journal of Operational Research, 255 (2).
Moshref Javadi, M., & Lehto, M. (2016). Material Handling Improvement in Warehouses by Parts Clustering. International Journal of Production Research, 54 (14), 4256-4271.
Jabal-Ameli, M., & Moshref Javadi, M. (2013). Concurrent Cell Formation and Layout Design Using Scatter Search. International Journal of Advanced Manufacturing Technology, 71 1-22.
Jabal-Ameli, M., Moshref Javadi, M., Bankian-Tabrizi, B., & Mohammadi, M. (2013). Cell Formation and Layout Design with Alternative Routing: A Multi-Objective Scatter Search Approach. International Journal of Industrial and Systems Engineering, 14 (3), 269-295.
Jabal-Ameli, M., Bankian-Tabrizi, B., & Moshref Javadi, M. (2011). A Simulated Annealing method to solve a generalized maximal covering location problem. International Journal of Industrial Engineering Computations, 2 (2), 439-448.
Moshref Javadi, M., Moqri, M., & Yazdian, A. (2011). Supplier selection and order lot sizing using dynamic programming. International Journal of Industrial Engineering Computations, 2 (2), 319-328.

Presentations

Moshref Javadi, M. (2023). How COVID-19 Changed Consumers’ Shopping Habits. POMS International Conference.
Moshref Javadi, M., Johannessen, P., & Hemmati, A. (2023). A Pickup and Delivery Problem with Multiple Time Windows and Resource Constraints. Canadian Operations Research Conference.
Moshref Javadi, M., Hemmati, A., & Winkenbach, M. (2020). Synchronizing truck and drones for last-mile delivery operations. INFORMS Annual Meeting.
Moshref Javadi, M., Hemmati, A., & Winkenbach, M. (2018). A Multi-Modal Drone Delivery System for Urban Logistics. INFORMS Annual Meeting.
Moshref Javadi, M., Hemmati, A., & Winkenbach, M. (2018). A Heuristic Method for a Customer-centric Drone Delivery System. IISE Conference.
Moshref Javadi, M., Lee, S., & Winkenbach, . (2017). The Customer-Centric Drone Delivery System. INFORMS Annual Meeting.
Moshref Javadi, M., & Lee, S. (2015). A Memetic Algorithm to Minimize Latency in Location Routing Problems. INFORMS Annual Meeting.
Moshref Javadi, M., & Lehto, M. (2014). Material handling improvement by parts clustering. INFORMS Annual Meeting.

Honors and Awards

Deloitte Scholar, University of Illinois at Urbana-Champaign, 2023 to present
Teachers Ranked as Excellent - Summer, University of Illinois at Urbana-Champaign, 2022, 2023
Specialized Faculty Outstanding Research Award, Gies College of Business, 2022
Teachers Ranked as Excellent - Fall, University of Illinois at Urbana-Champaign, 2021

Service

Reviewer, IEEE Transactions on Systems, Man and Cybernetics: Systems, 2024 to present
Reviewer, Sustainable Cities and Society, 2024 to present
Reviewer, Internet of Things, 2023 to present
Reviewer, Supply Chain Forum, 2023 to present
Reviewer, Cleaner Logistics and Supply Chain, 2022 to present
Reviewer, IEEE Transactions on Engineering Management, 2022 to present
Reviewer, PLOS ONE, 2022 to present
Reviewer, Research in Transportation Economics, 2022 to present
Reviewer, SoftwareX, 2022 to present
Reviewer, Technological Forecasting & Social Change, 2022 to present
Reviewer, Journal of Business Analytics, 2021 to present
Reviewer, Journal of Scheduling, 2020 to present
Reviewer, Engineering Optimization, 2019 to present
Reviewer, Expert Systems with Applications, 2018 to present
Reviewer, Production and Operations Management, 2018 to present
Reviewer, IET Intelligent Transport Systems, 2018 to present
Reviewer, Transportation Research Part C: Emerging Technologies, 2018 to present
Reviewer, Transportation Science, 2018 to present
Reviewer, International Journal of Production Research, 2017 to present
Reviewer, Transportation Research Part E: Logistics and Transportation Review, 2017 to present
Reviewer, Journal of the Operational Research Society, 2017 to present
Reviewer, Networks, 2017 to present
Reviewer, European Journal of Operational Research, 2017 to present
Reviewer, Computers and Operations Research, 2017 to present
Reviewer, Annals of Operations Research, 2017 to present
Reviewer, IEEE Transactions on Intelligent Transportation Systems, 2017 to present, 2017 to present
Session Chair for "Emerging Logistics Models", POMS International Conference, 2023
Session Chair for "Emerging Logistics Models", INFORMS, 2021, 2022
Session chair for "Autonomous Robots in Delivery Logistics", International Federation for Information Processing (IFIP), 2021
Session chair for "Last-mile logistics optimization", INFORMS, 2020

Teaching Interests

Business Analytics, Data Analytics, Decision and Management Sciences, Operations Management, Logistics Management, Supply Chain Management, Optimization, Simulation

Research Interests

Applied operations research, Data-driven decision making, and Mathematical modeling with applications to production systems, supply chain, and disaster relief operations, Sustainability, Artificial intelligence

Current Courses

Business Analytics II (BADM 211) Builds on the foundation from the Business Analytics I (BADM 210), synthesizes concepts through hands-on application and project-based learning. Focuses on data acquisition, organization, analysis and visualization in a business setting. Expanding on the use of statistics in generating basic inferences to predictive modeling Identify opportunities for improving business decisions using data, conduct relevant analysis of the gathered and cleaned data, and finally, interpret and present analysis outcomes to decision makers. Using statistical tools and software applications to identify business problems, acquire relevant data, and generate analytic solutions using advanced analytics techniques and tools for generating insights. Introduces the students to analyzing, learning, and prediction using advanced analytics techniques and tools for generating business insights. This course will provide a practical introduction to various techniques regarding clustering, text mining, classification and decision trees, and time series analysis. Finally, the course will introduce advanced and emerging topics in predictive analytics.
Operations Management (BADM 275) Operations Management is about developing, producing, and delivering goods and services that meet and exceed customer expectations. In this course, students will be introduced to decision making frameworks and techniques for effectively and efficiently managing operations through coordinated efforts across different organizations in a supply chain and across multiple areas within an organization. These multiple areas could be consumer analytics, research and development, finance, engineering, marketing, human resource management, sourcing, information systems, logistics, and accounting.
Operations Strategy (BADM 375) Students will learn how organizations can gain and sustain competitive advantage through their operations capabilities. The course content will cover manufacturing and service contexts across industries such as airline, consulting, entertainment, healthcare, hospitality, information technology, and retail. Cases and examples will be used to explore technologies such as blockchain and internet of things (IOT), issues such as supply chain risk and social responsibility, and business models such as alliances and sharing economy.
Business Process Modeling (BADM 460) Introduces the identification and analysis of various aspects of business processes. The course defines business processes and provides tools for designing and analyzing them.
Process Management (BADM 567) Operations Management (OM) is the design and execution of systems for the development, production, and distribution of goods and services. OM includes decisions for choosing production technologies, designing processes, creating demand forecasts, managing inventories, selecting suppliers, and ensuring quality. This course focuses on conceptual foundations and fundamental analytical approaches for OM.
Supply Chain Analytics (BADM 575) The objective of the course is to introduce students to using data analytics for improving decision making in supply chains. With Globalization and digitization of supply chains a large volume of data is getting generated within supply chains. Being able to use the information in the data to improve supply chain functioning is critical to success for many organizations. In this course, students are introduced to data analytic methods such as statistical modeling and machine learning methods for organization, and analysis of large volume of different kind of data that relate to specific aspects of managing and organizing supply chain. This course follows a project based practical learning approach. The course is divided into several modules and students are required to analyze and present data and inferences with respect to these modules. 4 graduate hours. No professional credit. Credit is not given for BADM 575 and BADM 590 (31474) Section SCA.