Qualification Type: | PhD |
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Location: | Glasgow |
Funding for: | UK Students, EU Students, International Students |
Funding amount: | Not Specified |
Hours: | Full Time |
Placed On: | 6th February 2023 |
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Closes: | 31st March 2023 |
Project summary: The project will investigate supply chain optimisation for complex multi-echelon operations under uncertainty, which can easily propagate in such a system. This is particularly challenging during emergency situations, whether local or global and can be sudden or predictable within a short time. The researcher is expected to develop mathematical optimization models and design customised algorithms to address these problems under various considerations.
Deadline: 31 March 2023
Duration: 36 months full-time
Funding details: Fully-funded scholarship for 3 years covers all university tuition fees (at UK level) and an annual tax-free stipend. International students are also eligible to apply, but they will need to find other funding sources to cover the difference between the home and international tuition fees. Exceptional international candidates may be provided funding for this difference.
Number of places: 1
Eligibility: 1st class honours/undergraduate degree (essential) and an excellent Masters-level qualification or equivalent (strongly desirable), in a highly quantitative subject such as Computer Science, Operations Research, Mathematics, Statistics, or Engineering. Proficient programming skills in an object-oriented programming language are highly desirable.
Project details: Existing methods of supply chain optimization for complex multi-echelon operations are often computationally expensive, and this problem is further complicated when uncertainties are involved, which propagate upstream or downstream in such a multi-echelon system. This becomes a particular challenge during emergency situations, which involves in finding an efficient transition to accommodate the new requirements of an emergency situation that 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 focussed 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. There is need to develop theory and mathematical models that perceives this as a multifaceted and integrated problem, as well as computational tools that maximize existing data analytics and algorithmic capabilities in the current data-driven world.
The project aims to attempt to address several research questions, such as:
We are interested in mathematically modelling these problems and designing customised algorithms and data analytics tools and perform extensive computational testing.
Primary supervisor: Professor Kerem Akartunali
Contact: kerem.akartunali@strath.ac.uk
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