vcc.ca
OPMT 2100: Knowledge Systems, Analytics, and Optimization Modeling
Effective date
January 2027
Department
Global Supply Chain Management
School
Hospitality, Food Studies and Applied Business
Description
This course examines how knowledge systems, data analytics, and optimization models support effective decision-making in modern supply chains. The first component focuses on knowledge management frameworks and digital information systems that enable organizations to capture, structure, share, and apply operational knowledge across complex supply networks. Students explore how data governance, enterprise systems, and decision-support technologies enhance coordination, visibility, and performance.
The second component introduces quantitative optimization techniques used to improve supply chain efficiency and resource allocation. Students apply tools such as linear programming, network modeling, forecasting, and scheduling methods to real-world operational challenges. The course also examines the emerging role of generative AI in modeling, simulation, and scenario analysis, enabling data-driven insights and adaptive decision-making. Through applied exercises, students develop practical skills in analyzing supply chain problems and designing optimized, technology-enabled solutions.
Credits
3.0
Year of study
2nd Year Post-secondary
Prerequisites
None
Corequisites
None
Course Learning Outcomes
Upon successful completion of this course, students will be able to:
- Describe the importance of Knowledge Management in Supply Chains
- Utilize Techniques for Knowledge Capture and Transfer as they apply to an organization or supply chain
- Integrate technology for Knowledge Management
- Apply the principles and techniques of knowledge mapping and analysis throughout a supply chain
- Apply organization learning and continuous improvement processes in maintaining quality, reliability and/or standards
- Create Linear Programming Models
- Apply various techniques to optimize efficiency such as Linear Programming, Dual, the Transportation Model, Assignment, and Scheduling
- Use Artificial Intelligence for scenario analysis, modeling, and optimization within supply chain processes
- Use Generative AI for conducting what-if scenarios within a digital twin environment, accurately reflecting real-world supply chain dynamics
Prior Learning Assessment & Recognition (PLAR)
None
Hours
Lecture, Online, Seminar, Tutorial: 45
Total Hours: 45
Total Hours: 45
Instructional Strategies
Lectures, case-studies, groupwork
Grading System
Letter Grade (A-F)
Passing grade
D
Evaluation Plan
|
Type |
Percentage |
Assessment activity |
|
Midterm Exam |
15-20 |
|
|
Final Exam |
25-30 |
|
|
Assignments |
20-30 |
Individual and group assignments |
|
Quizzes/Tests |
20 |
Two or more quizzes |
|
Participation |
10 |
|
Course topics
- Fundamentals of Knowledge Management in Supply Chains Techniques for Knowledge Capture and Transfer Technology Integration for Knowledge Management Knowledge Mapping and Analysis in Supply Chains Organizational Learning and Continuous Improvement Linear Programming Fundamentals Dual for linear programming model Transportation models Assignment and Scheduling Intellectual Property (IP), legal and ethical considerations in knowledge management and knowledge sharing
Notes:
- Course contents and descriptions, offerings and schedules are subject to change without notice.
- Students are required to follow all College policies including ones that govern their educational experience at VCC. Policies are available on the VCC website at:
https://www.vcc.ca/about/governance--policies/policies/. - To find out if there are existing transfer agreements for this course, visit the BC Transfer Guide at https://www.bctransferguide.ca.