Module manager: Davood Shiri
Email: D.Shiri@leeds.ac.uk
Taught: Semester 2 (Jan to Jun) View Timetable
Year running 2026/27
This module is not approved as an Elective
This module provides a rigorous and comprehensive introduction to the analytical and quantitative foundations of modern operations, logistics and supply chain management. Students will develop skills in analytics and decision modelling, tailored to evaluate and improve complex operational systems. Core topics include supply chain applications of demand forecasting, linear and integer programming, network flows and network design models, facility location, pricing analytics, transportation planning, inventory management, warehousing, vehicle routing and scheduling. In addition to the theoretical foundations, students engage with practical exercises and real-world data to understand how analytical tools can address genuine organisational challenges and generate measurable improvements in efficiency, resilience and decision quality. This enables them to apply these methods in real-life contexts while strengthening both their disciplinary knowledge and employability skills. The module is ideal for students aiming to build strong analytical capabilities and pursue careers as supply chain analysts, supply chain and logistics planners, and supply chain consultants.
The module will equip students with a strong analytical foundation for understanding, modelling and improving operations and supply chain systems. It seeks to develop students’ ability to apply quantitative methods, optimisation techniques and data-driven analytical approaches, supported by appropriate programming languages and computational tools, to real organisational challenges. Through a combination of lectures, practical exercises, hands-on analytical work and problem-based learning, the module enables students to interpret operational data, evaluate alternative decisions and justify evidence-based solutions. By integrating theory with applied learning, the module prepares students to critically assess operational performance, design effective supply chain strategies, and develop the analytical capabilities required for professional roles as analysts and consultants in operations, logistics and supply chain management.
On successful completion of the module students will be able to:
ALO1- Critically evaluate the theoretical foundations of quantitative methods used in operations, logistics and supply chain management.
ALO2- Formulate and apply mathematical models across a range of supply chain problems (e.g. network design, location analysis, transportation planning, inventory management, warehousing, routing and scheduling) while accurately interpreting problem components and their practical applications.
ALO3- Design and develop various solution algorithms, including heuristic methods, to solves supply chain problems.
ALO4- Evaluate and compare the quality, robustness, and suitability of different solution techniques for diverse supply chain problem settings.
ALO5-Interpret analytical outputs from predictive and prescriptive analytics to compare alternative operational and supply chain decisions and justify evidence-based recommendations.
On successful completion of the module students will be able to:
SLO1- Identify the most suitable analytics tools to tackle logistics and supply chain problems, identifying key operational challenges, goals, constraints, and decision requirements to inform evidence-based strategies.
SLO2-Design and implement mathematical models and appropriate solution algorithms, utilising Python and Excel solver tools to generate actionable insights and enhance supply chain performance.
SO3- Interpret analytical results to generate actionable insights that support supply chain decision-making.
SLO4- Present the results of predictive and prescriptive analytics in written report.
| Delivery type | Number | Length hours | Student hours |
|---|---|---|---|
| Workshop | 8 | 2 | 16 |
| Lecture | 9 | 2 | 18 |
| Private study hours | 116 | ||
| Total Contact hours | 34 | ||
| Total hours (100hr per 10 credits) | 150 | ||
Formative feedback on the coursework will be provided through feedback on optional coursework proposals submitted via Minerva. The proposal is not a mandatory or graded component; rather, it provides students with an opportunity to receive early feedback on their topic, methodology, and problem formulation before submitting the final coursework. This allows students to build on what is covered in lectures and seminar sessions by applying the concepts to their own coursework topic and receiving guidance at an early stage. In addition, in-class quizzes conducted during lecture and seminar sessions will provide further opportunities for formative feedback, with feedback provided during the sessions. Seminar activities will also incorporate structured formative feedback to support students in developing their understanding and applying this feedback to their coursework.
| Assessment type | Notes | % of formal assessment |
|---|---|---|
| Assignment | 3,000 words | 100 |
| Total percentage (Assessment Coursework) | 100 | |
The resit for this module will be 100% by 3,000 word assignment.
Check the module area in Minerva for your reading list
Last updated: 30/04/2026
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