MSc. Thesis Defense: Neman Karimi, A Dynamic Strategic Plan for the Transition to a Clean Bus Fleet Using Multi-Stage Stochastic Programming

A Dynamic Strategic Plan for the Transition to a Clean Bus Fleet Using Multi-Stage Stochastic Programming

Neman Karimi
Industrial Engineering, MSc. Thesis, 2025

Thesis Jury

Assoc. Prof. Burak Kocuk (Thesis Advisor)

Asst. Prof. Tuğçe Yüksel (Thesis Co-Advisor),

Asst. Prof. Esra Koca,

Prof. Taner Bilgiç,

Asst. Prof. Sakine Batun

Date & Time: July 11th, 2025 –  1 PM

Place: FENS - 2019

Keywords : Bus fleet transition, Zero-emission vehicles, Sustainability, Strategic Planning, Multi-stage stochastic programming

Abstract

In recent years, the transition to clean bus fleets has accelerated. Although this transition might bring environmental and economic benefits, it requires a long-term strategic plan due to the large investment costs involved. This thesis proposes a multi-stage stochastic program to optimize strategic plans for the clean bus fleet transition that explicitly considers the uncertainty scenarios in the cost and efficiency improvements of clean buses.

Our optimization model minimizes the total expected cost subject to emission targets, budget restrictions, and several other operational considerations. We propose a new forecasting approach that captures the correlation between these improvements to obtain realistic future pathways for Battery Electric Buses (BEBs) and Hydrogen Fuel Cell Buses (HFCBs), which are then given to the multi-stage stochastic program as scenarios. We also utilize a physics-based model for BEBs to accurately capture their energy consumption and recharging needs. As a case study, we focus on the complex public bus network of Istanbul, which aims to transition to a clean bus fleet by 2050. Utilizing real datasets, we solve a five-stage stochastic program spanning a 25-year planning horizon that involves 256 scenarios to obtain dynamic strategic plans that can be used by policymakers. 

Our results suggest that BEBs are more advantageous than HFCBs, even in slow BEB but fast HFCB development scenarios. We also conduct several sensitivity analyses to understand the effects of intermediate emission targets, budget limitations, and energy prices.