The University of Strathclyde is providing a scholarship for a project that aims to investigate strategies for improving the effectiveness of complex multi-level supply chain operations while considering the impact of uncertainty, which can rapidly propagate throughout the entire system. This becomes particularly challenging in situations of unforeseen or anticipated emergencies, whether they arise locally or globally and with or without prior notice. The researcher’s responsibility is to develop mathematical optimization models and customized algorithms that can address these challenges while considering multiple variables.
Funding Details
Fully-Funded Scholarship for 3 Years
The project offers a fully-funded scholarship for three years, which covers all university tuition fees at the UK level. In addition, a tax-free stipend will be provided annually.
Eligibility for International Students
International students are also welcome to apply for the scholarship. However, they will need to find additional funding sources to cover the difference between the home and international tuition fees.
Exceptional International Candidates
Exceptional international candidates may be provided with funding to cover the difference in tuition fees between home and international rates.
Eligibility
Applicants must possess a first-class honours undergraduate degree, which is essential for this position. In addition, a highly quantitative subject such as Computer Science, Operations Research, Mathematics, Statistics, or Engineering is strongly desirable. Candidates with an excellent Masters-level qualification or equivalent are also preferred.
Proficient programming skills in an object-oriented programming language are highly desirable and will be considered an advantage.
Project details
The current methods used for optimizing supply chains in complex multi-echelon operations are often computationally expensive. Furthermore, when uncertainties are present, they can propagate upstream or downstream in the multi-echelon system, further complicating the problem. This can become particularly challenging during emergency situations as there is a need to find an efficient transition that can accommodate the new requirements of the situation. These emergency situations can be either local (e.g. floods, forest fires) or global (e.g. pandemics) and can be sudden (e.g. earthquakes) or predictable within a short time frame (e.g. pandemic, hurricanes).
Supply chain emergency response management has traditionally focused on individual dimensions such as agility, risk/knowledge management, operational planning (e.g. logistics, facility location, or inventory management), humanitarian issues, and multi-level integration. However, there is a need to develop a theory and mathematical models that perceive this as a multifaceted and integrated problem. Additionally, computational tools are required to maximize existing data analytics and algorithmic capabilities in the current data-driven world.
The objective of this project is to investigate several research questions, including:
- Do cooperative strategies provide superior benefits in post-disaster supply chain planning?
- What is the most effective recovery time that can be achieved in the event of a disaster?
- How can challenging decisions such as selecting which customers/products to serve be incorporated?
We aim to mathematically model these issues, develop custom algorithms and data analytics tools, and conduct extensive computational testing. Professor Kerem Akartunali is the primary supervisor for this project, and they can be reached at [email protected].
Deadline: 31 March 2023
