Overview and Rationale
This assignment is designed to provide you with hands-on experiences to optimize shipments via non-linear programming models in real-life applications. You are provided with a logistics scenario and you are asked to create a model to optimize cost and distribution of shipments. You are also asked to apply the Hodrick-Prescott Filter to a time series stock data.
Course Outcomes
This assignment is directly linked to the following key learning outcomes from the course syllabus:
CO1: Use descriptive, Heuristic and prescriptive analysis to drive business strategies and actions
CO4: Incorporate general industry practices in end-to-end analytics development cycles, including data management, data engineering, analytics modeling, optimization, and strategic development
Discuss the influence the decision-making process had on the outcome.
October 16, 2017
12:00 pm
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