danjeffrey/modeling-examples

Gurobi modeling examples

Gurobi modeling examples

Introduction:

Target audience:

Data scientists, engineers, computer scientists, economists, and in general, professionals with background on mathematical modeling and basic knowledge of Python.

Goals of modeling examples:

• Illustrate broad applicability of mathematical optimization.
• Show how to build mathematical optimization models.

Modeling examples are coded using the Gurobi Python API in Jupyter Notebook.

The modeling examples illustrate important features of the Gurobi Python API modeling objects such as adding decision variables, building linear expressions, adding constraints, and adding an objective function for a mathematical optimization model. In addition, they explain more advanced features such as generalized constraints, piece-wise linear functions, multi-objective hierarchical optimization, as well as “typical” type of constraints such as “allocation constraints”, “balance constraints”, “sequencing constraints”, “precedence constraints”, etc. In addition, these modeling examples show how the modeling objects of Gurobi and the typical type of constraints can be used in different contexts.

Index of modeling examples

• Customer Assignment
• H.P. Williams
• Innovation Portfolio Optimization
• The Lasso
• L0-Regression
• Resource Management Optimization
• Traveling Salesman Problem
• Workforce Scheduling

These modeling examples are distributed under the Apache 2.0 license, (c) copyright 2019 Gurobi Optimization, LLC