11/15/2024
By Danielle Fretwell

The Francis College of Engineering, Department of Civil and Environmental Engineering, invites you to attend a Doctoral Dissertation defense by Majed K. Abdulghani on: Multi-Objective Risk Optimization Model for Medical Waste Collection in Urban Environments

Candidate Name: Majed K. Abdulghani
Degree: Doctoral
Defense Date: Wednesday, November 20, 2024
Time: 12 - 2 p.m.
Location: Remote. Please email the advisor (Polichronis_Stamatiadis@uml.edu) and student (Majed_Abdulghani@student.uml.edu) for link.

Committee:
Advisor: Polichronis Stamatiadis Ph.D., Associate Professor, Civil and Environmental Engineering, UMass Lowell

Committee Members*
1. Nathan H. Gartner, Sc.D., Professor Emeritus, Civil and Environmental Engineering, UMass Lowell
2. Yuanchang Xie Ph.D., Professor, Civil and Environmental Engineering, UMass Lowell
3. Badr O. Johar Ph.D, CEO, Mechanical and Industrial Engineering, Northeastern University

Brief Abstract:
This dissertation proposes a Multi-Objective Optimization model for addressing the challenges in current medical waste management systems in rapidly developing urban settings. Rapid urbanization, driven by the increasing difficulty of waste management in healthcare facilities, poses significant risks to public health and the environment. To confront these challenges, this research develops an optimization model for the collection and transportation of medical waste from a variety of healthcare facilities.

The model balances the dual objectives of minimizing operational costs, as well as, of minimizing risks associated with untimely waste collection and addressing economic and public health concerns. It employs a mixed-integer linear programming (MILP) approach, computational productivity, and scalability using decomposition strategies and parallel computing.

An extensive case study of several healthcare institutions in a rapidly growing urban area thoroughly appraised the model's effectiveness. The results confirmed substantial improvements over existing methods in risk reduction.