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.
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 descri…
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…
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 th…
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…
Some points apply to every course of this kind; see how we rank.
University of California, Irvine is in Tier 2: excellent universities and the companies that build the technology of our institution ranking (82/100).
Instructor: Prof. Gary Gensler View the complete course: https://ocw.mit.edu/15-S12F18 This course is for students wishing to explore blockchain technology’s potential use - by entrepreneurs & incumbents - to change the world of money and finance. License: Creative Commons BY-NC-SA More information…
This course provides an introduction to mathematical modeling of computational problems. It covers the common algorithms, algorithmic paradigms, and data structures used to solve these problems. The course emphasizes the relationship between algorithms and programming, and introduces basic performa…
This is CS50P, CS50's Introduction to Programming with Python. Register for free at https://cs50.edx.org/python. Slides and source code at https://cs50.harvard.edu/python. Playlist at https://www.youtube.com/playlist?list=PLhQjrBD2T3817j24-GogXmWqO5Q5vYy0V. An introduction to programming using a la…
This is CS50, Harvard University's introduction to the intellectual enterprises of computer science and the art of programming, for concentrators and non-concentrators alike, with or without prior programming experience. (Two thirds of CS50 students have never taken CS before.) This course teaches…
Instructor: Ana Bell View the complete course: https://ocw.mit.edu/courses/6-100l-introduction-to-cs-and-programming-using-python-fall-2022/ *Note: Lectures 6, 10 have been updated! This subject is aimed at students with little to no programming experience. It aims to provide students with an under…
Get more information about the courses and programs we offer. In this playlist you can learn more about course content, pricing, credentials and more!
