Multi-Objective Optimization Framework for Electrified Vehicle Penetration Based on Life Cycle Assessment and Life Cycle Cost.
This research proposed a novel framework for creating optimal transportation scenarios that consider multiple objectives such as minimum greenhouse gas emissions, air pollutant levels, and cost of ownership. The thesis approach is a multi-objective evolutionary algorithm coupled with the AFEET tool, allowing us to efficiently explore the complex trade-offs between these objectives and identify a diverse set of optimal solutions. Through several case studies and a design of experiments, this demonstrates the effectiveness and practicality in different scenarios. This approach has significant implications for policymakers and industry professionals seeking to make sustainable and cost-effective decisions in the transportation sector.
Diaz Lozano, Eva Alondra, "Multi-Objective Optimization Framework for Electrified Vehicle Penetration Based on Life Cycle Assessment and Life Cycle Cost." (2023). ETD Collection for University of Texas, El Paso. AAI30493151.