Technician Routing and Scheduling Problem
Try this modeling example to discover how mathematical optimization can help telecommunications firms automate and improve their technician assignment, scheduling, and routing decisions in order to ensure the highest levels of customer satisfaction.
Refinery Planning
In this example, we’ll demonstrate how you can use mathematical optimization to optimize the output of a refinery. You’ll learn how to generate an optimal production plan that maximizes total profit, while taking into account production capacity and other restrictions.
Opencast Mining
How can a mining company use mathematical optimization to identify which excavation locations to choose in order to maximize the gross margins of extracting ore? Try this modeling example to find out!
Mining
Put your planning skills to the test in this example, where you’ll learn how to model and solve a production planning problem that involves optimizing the operations of a group of mines over a five-year period.
Logical Design
This problem is an example of constructing a circuit using the minimum number of NOR gates (devices with two inputs and one output) that will perform the logical function specified by a truth table. This problem is formulated as a binary optimization problem using the Gurobi Python API and solved with the Gurobi Optimizer.
Food Manufacturing
If you’re hungry for a mathematical optimization challenge, then try this food manufacturing problem. You’ll learn how to create an optimal multi-period production plan for a product that requires a number of ingredients – each of which has different costs, restrictions, and features.
Factory Planning
Want to learn how to create an optimal production plan that will maximize your profits? In this example, we’ll teach you how to solve this classic production planning problem.
Electrical Power Generation
Major electric power companies around the world utilize mathematical optimization to manage the flow of energy across their electrical grids. In this example, you’ll discover the power of mathematical optimization in addressing a common energy industry problem: electrical power generation. We’ll show you how to figure out the optimal set of power stations to turn on in order to satisfy anticipated power demand over a 24-hour time horizon.
Customer Assignment
Sharpen your mathematical optimization modeling skills with this example, in which you will learn how to select the location of facilities based on their proximity to customers. We’ll demonstrate how you can construct a mixed-integer programming (MIP) model of this facility location problem, implement this model in the Gurobi Python API, and generate an optimal solution using the Gurobi Optimizer.
Best Feature Selection for Forecasting
In this example, you will learn how to perform linear regression with feature selection using mathematical programming. We’ll show you how to construct a mixed-integer quadratic programming (MIQP) model of this linear regression problem, implement this model in the Gurobi Python API, and generate an optimal solution.
