A comprehensive technical handbook covering mathematical optimization with Gurobi Optimizer, from linear programming fundamentals to advanced techniques including integer programming, quadratic optimization, constraint modeling, and enterprise deployment.
Chapters
Setting Up Your Development Environment
10 min read
Linear Programming Fundamentals
20 min read
Modeling with Gurobi APIs: Python and Beyond
25 min read
Working with Variables, Constraints, and Objectives
20 min read
MIP: Mixed-Integer Programming Basics
25 min read
Advanced Constraint Modeling Techniques
25 min read
Quadratic Programming and Second-Order Cone Programming
20 min read
Understanding the Gurobi Solver Engine and Algorithms
20 min read
Presolve, Heuristics, and Cutting Planes
25 min read
Debugging Infeasible and Unbounded Models
20 min read
Performance Tuning and Parameter Settings
25 min read
Multi-Objective Optimization
15 min read
Global Optimization for Non-Convex Problems
20 min read
Working with Large-Scale Data and Sparse Matrices
20 min read
Callbacks and Custom Solver Logic
25 min read
Parallel Processing and Distributed Optimization
20 min read
Enterprise Deployment and API Best Practices
20 min read
Integrating Gurobi with Machine Learning Pipelines
25 min read
Career Roadmap: Becoming an Optimization Expert
15 min read