Francisca Ignacia Urrutia Diaz
Developing an Optimization Model for the Mixed Fleet Electric Vehicle Scheduling Problem (MF-EVSP).
Rel. Fabio Guido Mario Salassa. Politecnico di Torino, Master of science program in Engineering And Management, 2025
|
Preview |
PDF (Tesi_di_laurea)
- Thesis
Licence: Creative Commons Attribution Non-commercial No Derivatives. Download (10MB) | Preview |
Abstract
Meeting the growing demand for greener city transport calls for fresh ideas that make the most of what cities already own while still leaving room for new tech. The work presented here builds a Mixed-Integer Linear Programming (MILP) model that runs urban bus fleets as a single, unified system. Rather than focusing on an all-electric future, the approach recognises todays mixed fleets, pairing electric buses with diesel units so cities dont lose service during the changeover. A standout feature is real-time battery tracking, which fuels smart charging choices and double-checks that every bus can finish its planned trip. The model also weaves in standard transport rules-route assignment, travel times, service hours, and depot space-so the results fit everyday operations.
Relators
Academic year
Publication type
Number of Pages
Course of studies
Classe di laurea
URI
![]() |
Modify record (reserved for operators) |
