The MILP Optimization Handbook: A Comprehensive Guide to Mixed-Integer Linear Programming, Algorithms, and Real-World Applications - Couverture souple

Parks, Brandon A.

 
9798264331756: The MILP Optimization Handbook: A Comprehensive Guide to Mixed-Integer Linear Programming, Algorithms, and Real-World Applications

Synopsis

A complete, modern guide to Mixed-Integer Linear Programming (MILP)—from fundamentals to advanced modeling and real-world applications.

Whether you’re a student, data scientist, or optimization professional, this handbook provides a clear, practical roadmap through every aspect of MILP modeling and algorithm design.
Written in accessible language, it combines rigorous mathematics with hands-on examples using open-source tools like Pyomo, CBC, and OR-Tools.

Inside you’ll find:

🔹 Part I – Foundations

Learn the essentials of linear and integer programming, model formulation, and convexity.
Understand how constraints, objectives, and relaxations form the mathematical core of decision-making.

🔹 Part II – Algorithms and Solvers

Explore the inner workings of branch-and-bound, cutting planes, Lagrangian relaxation, and decomposition methods.
Includes pseudocode, solver strategies, and step-by-step explanations of how MILP engines think.

🔹 Part III – Modeling and Applications

Translate theory into practice across real domains:
scheduling, facility location, logistics, finance, energy planning, and even machine learning.

🔹 Part IV – Advanced Topics

Discover how modern MILP handles uncertainty, large-scale data, and hybrid optimization with heuristics and machine learning.
Includes introductions to decomposition, stochastic MILP, robust optimization, and metaheuristics.

🔹 Appendices and Templates

Quick-reference installation guides for major solvers, reusable Pyomo templates, a complete notation index, and a curated bibliography of essential MILP references.

By combining clarity, rigor, and real-world focus, The MILP Optimization Handbook bridges the gap between theory and implementation—making it an indispensable reference for anyone working in operations research, applied mathematics, AI optimization, or industrial analytics.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.