GRA 6753 Operations Management
GRA 6753 Operations Management
In the evolving field of operations management and logistics, a deep understanding of optimization strategies is essential for minimizing costs, enhancing service levels, and maximizing efficient resource use. This course equips students with the skills to make strategic operational decisions in logistics, focusing on predictive and prescriptive models. Emphasizing sustainability, students learn to plan resource use effectively within the constraints of resource scarcity, aligning with significant sustainability goals and the principles of the circular economy.
- Understand the role of decision support systems in enhancing supply chain management.
- Connect course topics with broader societal issues, understanding the impact on business, economy, production, transportation, environment, and society, and aligning efforts with UN's Sustainable Development Goals 8 (Decent Work and Economic Growth), 9 (Industry, Innovation, and Infrastructure), and 12 (Responsible Consumption and Production).
- Employ Excel Solver for optimization and decision-making models.
- Analyze capacity and identify bottlenecks in processes.
- Forecast demand and sales within supply chains.
- Develop and optimize aggregate production plans.
- Design pricing and overbooking strategies for various market segments.
- Manage and optimize inventory policies for both cycle and safety stock.
- Appreciate the capabilities and limits of optimization models.
- Address everyday challenges in logistics and supply chain management.
- Identify, develop, and evaluate models and solutions for optimization, planning, and operational decision-making challenges in supply chain management, integrating sustainability into these processes.
- Introduction to operations management and the principles of optimization.
- Evaluating supply process capacity and optimizing supply chain flow.
- Techniques for demand forecasting
- Aggregate production planning models.
- Strategies for cycle and safety inventory management, including discount and optimal service level considerations.
- Approaches to pricing and revenue management.
The course combines theoretical foundations with practical application, predominantly delivered through a hands-on, learning-by-doing approach in a Microsoft Excel environment. Students will build and extend models in Excel, enhancing their learning with exercises both in and out of class.
Students are required to bring a computer with Microsoft Excel installed to all lectures.
It is the student's responsibility to catch up on any class-provided information.
All courses in the Masters programme will assume that students have fulfilled the admission requirements for the programme. In addition, courses in second, third and/or fourth semester can have specific prerequisites and will assume that students have followed normal study progression. For double degree and exchange students, please note that equivalent courses are accepted.
Disclaimer
Deviations in teaching and exams may occur if external conditions or unforeseen events call for this.
- Proficiency in basic Microsoft Excel functions, including formula entry, and the use of relative and absolute cell references.
- Although basic Excel courses are available through BI, students are encouraged to utilize free resources like Trump Excel for self-study, which offers comprehensive tutorials and exercises.
| Assessments |
|---|
Exam category: Submission Form of assessment: Submission PDF Exam/hand-in semester: First Semester Weight: 100 Grouping: Individual Duration: 5 Hour(s) Comment: The assessment is in the form of open-book home exam due to use of Excel. Exam code: GRA 67531 Grading scale: ECTS Resit: Examination when next scheduled course |
| Activity | Duration | Comment |
|---|---|---|
Teaching | 24 Hour(s) | participation in the class |
Student's own work with learning resources | 12 Hour(s) | Asynchronous lectures |
Student's own work with learning resources | 48 Hour(s) | Reading textbook and lecture notes and watching uploaded videos |
Individual problem solving | 60 Hour(s) | Solving/completing given exercises at home |
Examination | 5 Hour(s) | |
Prepare for teaching | 12 Hour(s) | Go through lecture notes and selected textbook sections before the synchronous lecture in the class |
A course of 1 ECTS credit corresponds to a workload of 26-30 hours. Therefore a course of 6 ECTS credits corresponds to a workload of at least 160 hours.