Optimization is an important piece of an agile supply chain. In this course, we will explore the components of optimization and how to set up an optimization problem in Excel. We will also practice capacity and resource optimization and explore examples of both in the supply chain. Building off of our optimization practice, we will next learn how to use a Monte Carlo simulation to make the least risky decision in uncertain supply chain situations. Finally, we will combine our skills from this and the previous two courses to build a demand and inventory snapshot and optimize it, using a Monte Carlo simulation, to mitigate risks in the supply chain.
Overview
Syllabus
- Optimization Defined
- Welcome to Module 1, Optimization Defined. The word optimization has filled our lives in the last decade. Everywhere we turn, we either hear or see the word optimization, especially for those involved in marketing, supply chain, and operations. In this module, we will define optimization and describe its purpose in the supply chain. We will also identify the components of an optimization algorithm and see how to use an objective function in Excel. In our activity, we will practice formulating a maximization function.
- Capacity Optimization
- Welcome to Module 2, Capacity Optimization. In the previous module, we described optimization in general and saw how to set up an optimization problem in Excel. Over these next two modules, we will dive into two specific examples of optimization: capacity optimization and resource optimization. In this module, we will identify the goal of capacity optimization and overview some examples of how it can be used in the supply chain. We will also demo the steps to create a capacity optimization problem in Excel and recall these steps for our quiz. In our activity, we will describe how everyday tasks or functions can benefit from capacity optimization.
- Resource Optimization
- Welcome to Module 3, Resource Optimization. In this module, we will identify the goal of resource optimization, how it differs from capacity optimization, and go through some industry examples. We will learn how to set up a resource optimization problem in Excel through our demo video and recall these steps in our quiz. Finally, we will put what we’ve learned into practice by setting up and solving a resource optimization problem in Excel.
- Monte Carlo Simulation
- Welcome to Module 4, Monte Carlo Simulation. In this module, we will define a Monte Carlo simulation and when it should be used. Through our demo video, we will learn how to set up a Monte Carlo simulation in Excel, which will prepare us to identify the key inputs and Excel features needed to run a Monte Carlo simulation for our quiz. As a close to this specialization, this module has a peer-graded assignment. In our assignment, we will practice the skills learned in all three courses to build a demand and inventory snapshot and then use a Monte Carlo simulation to minimize costs. Finally, in our discussion, we will reflect on how skills learned through the past three courses can be applied to our current or future careers.
Taught by
Paul Jan
