ORIE 5213

Discrete Optimization for Urban Planning and Mobility

Course Description

Course information provided by the 2025-2026 Catalog.

The course is organized around five major case studies on the use of discrete optimization and data (AI at large) for smart cities. Namely, 1) bike sharing, 2) bus transportation planning, 3) fairness in ambulance allocation (and police patrol), 4) downed tree reporting (NYC Department of Parks and Recreation), and 5) parcel delivery.The teaching is structured to provide three levels of understanding: a first level in which the problem is presented with its importance, impact, and characteristics. The need of a tech-based quantitative approach is claimed and justified. A second level in which, a high-level version of the algorithmic approach used to solve the problem is presented. A third level, dependent on students' interest and knowledge, in which the algorithmic approach is detailed.

Prerequisites basic knowledge of linear algebra and data management.

Last 4 Terms Offered 2025SP, 2023SP

Outcomes

• Students will learn real case studies on modern city development, planning, and management. The three-level teaching structure should allow (i) the technically-oriented students to see how to use their competences on real-world problems, and (ii) the more domain-oriented students to be alerted at looking for technical solutions and recognize their need.

View Enrollment Information