LOG904-127 Last Mile Delivery: Data Analytics and Models (Autumn 2022)

About the course

Last-mile delivery, the final component of the supply chain, has the mission of achieving the ultimate objective of delivering goods to customers. It constitutes one of the more complex stages of the whole chain and accounts for a significant fraction of its total cost. Its complexity is a consequence of the specific conditions of the scenarios in which it is done: the urban environments, the factors determining how it is done, e.g. the ad hoc interaction between the implied stakeholders, shippers, carriers, administration and residents, and the peculiarities of the demand and its current trends resulting from the growth of e-commerce.

Planning and operating Last-Mile Deliveries must be supported by suitable Decision Support Systems (DSS) accounting for the peculiarities of the applications. Such DSS must be based on robust models to make planning decisions (i.e. demand analysis, customer profiles, location of City Distribution Centers, local satellites, etc., and the organizational structures) as well as operational (i.e. orders’ acceptance, time-dependent routing, etc.). Models must be fed with appropriate data whose availability depends on the technologies, data collection processes, and, namely, ad hoc data analytics techniques to extract the information and knowledge to build and apply the models.

The seminar will provide an outline of the last mile delivery systems, their organizational structures, the data and models to support planning and operational decisions, and the techniques to deal with them.

The course is connected to the following study programs

• Master of Science in Logistics
• Experience-based Master in Logistics
• Master of Science in Sustainable Energy Logistics
• Exchange programme - Master's level
• Master of Science in Sustainable Transport and Urban Mobility

Recommended requirements

Optimization Modeling, Vehicle Routing, Locational Models, Applied Statistics, Data Analytics (Principal Components Analysis, Clustering techniques, Data Mining)

The student's learning outcomes after completing the course

The student’s learning outcomes after completing the course:

Knowledge:

After completing the seminar will have acquired the knowledge to:

• Analyze the Last-Mile Delivery and identify which are the type of decisions to make to appropriately design it from the planning and operational perspectives

• Identify the characteristics and constraints and propose an organizational scheme (two-tier, or multi-tier depending on the circumstances

• Identify the data requirements, the technologies enabling the data collection, and the techniques to process the data to generate the required inputs to the decision models, especially for the real-time management operations

• Identify the appropriate models for each type of a decision, strategic, tactical, or operational

Skills:

After completing the course, the students will be able to apply the knowledge achieved:

• To implement the data collection process depending on the available technologies

• To apply the data analytics techniques to extract the necessary information and generate the appropriate inputs

• To analyze and interpret the generated information

• To apply the decision support models to find solutions

• To identify the requirements to implement in practice the solutions found

General competence:

After completing the course, the students should be able

• To apply the acquired knowledge to Last-mile Delivery applications in research and work contexts

• To design a full project through its various steps and a work plan to implement it

• To propose and conduct its realization with standard software tools for Geographic Information Systems, Optimization, and Data Analytics

• To critically analyze and interpret the solutions found, to propose a workable solution in a work context

• To criticize the advantages and disadvantages of the existing commercial software platforms for Logistics Analytics.

Forms of teaching and learning

Lecturing full days from Monday to Wednesday. Lectures will be based on:

 

• The material, slides, reports, and other written material, that will be provided to the students on the first day

• The discussion of use cases from real projects, and ad hoc pilots from the various projects of the European Union R&D Programs on Urban Logistics

Examination

• Form of assessment: A written assignment (a short essay) of at least 6000 words, based on the material made available to students at the beginning of the seminar (although if the student decides to base his/her essay on the discussion of a use case, he /she can use their own material). The essay should critically analyze (that is, the report should refñect his/her own opinion) the approaches taken, the data collected and how have been collected, the techniques and models used, how have they been used, and the results obtained and the solution proposed.

• Proportion: 100 %

• Duration: Until Saturday at 23:59

• Grouping: Individually

• Grading scale: Letter (A - F)

• Support material: The teaching and reading material provided to the students.