The Best New Linear Programming eBooks To Read In 2025

"Linear Programming for Decision-Making: A Practical Guide with Julia, R, and Python" by William Sewell immerses readers in the transformative optimization field through linear programming. Beginning with the seminal contributions of George Dantzig and Leonid Kantorovich, Sewell traces the evolution of these mathematical theories from their origins in mid-20th-century industrial and economic challenges. The book unveils the foundational principles of linear programming, illustrating how it optimally allocates scarce resources to maximize efficiency and outcomes.

Sewell integrates practical applications across diverse fields—from military logistics and telecommunications to modern-day global supply chains. By emphasizing the application of Julia, R, and Python programming languages, Sewell equips readers with the tools to effectively implement and utilize these powerful mathematical models in contemporary settings. Beyond theoretical exploration, Sewell introduces readers to pioneering figures who have leveraged linear programming to solve complex real-world problems, highlighting their successes and the enduring impact of their innovations. Whether you're a novice exploring the fundamentals or a seasoned professional seeking advanced insights, this book is a comprehensive guide to harnessing the power of optimization for informed decision-making.

In this book, I will teach you a Swiss army knife. But not one of those alpine products that these days come with pliers, a USB flash drive, and in a not-so-distant future, maybe with artificial intelligence. I will teach you a programming technique with which you can compute optimal solutions for highly complex optimization problems. In many cases really fast, like in less than a second. This technology is linear and integer programming!

Learning it can help youadvance in your careerfind better and fairer solutions for the company or organization you work forsave time in finding a good solutionuse resources more efficientlymake better business decisionsand yes, make the world a better place to be. In this book, we will cover the following:learn with examples how to use linear and integer programming to model optimization problemsgeneral techniques and useful tricks to model real-world problemssolving linear and integer programs with Microsoft Excel: build a spreadsheet to find the solutionwriting Python programs that compute the solution for youthe entire Python code for all examples is contained in the book and explained step by steponly very basic skills in Microsoft Excel and Python are requiredthe whole content is thoroughly explained and easy to follow. We will do everything from A to Z, so you do not need to know anything about linear and integer programming yet. In the end, you will be able to solve complex problems using Python and Microsoft Excel. Let’s get started!

Description:. The booklet titled "Linear Programming: A Comprehensive Guide" is an invaluable resource for individuals seeking a thorough understanding of linear programming techniques. With 64 pages of concise and well-organized content, this booklet serves as a comprehensive reference for both beginners and experienced practitioners of linear programming. Specifications:. Page Count: The booklet consists of 64 pages, providing ample space for in-depth explanations, examples, and illustrations. Dimensions: Measuring 8.5 x 11 inches, the booklet is designed to fit standard letter-size paper, making it easy to read and handle.

Content Overview:. Some Definitions: This section introduces essential terminology and concepts related to linear programming, providing readers with a solid foundation for further exploration. Graphical Method of Solving Linear Programming: Exploring the graphical approach, this chapter illustrates how linear programming problems can be solved by graphing the constraints and identifying the optimal solution. Corner Point Method: This method delves deeper into finding the optimal solution by analyzing the corner points of the feasible region, offering an alternative approach to graphical solving. Iso-Profit or Iso-Cost Method (Maximum Z): This section focuses on maximizing the objective function (Z) under given constraints, considering profit or cost as the primary objective. Iso-Profit or Iso-Cost Method (Minimum Z): In contrast to the previous section, this part emphasizes minimizing the objective function (Z), allowing readers to optimize their resources and costs effectively. Corner Point Method: This chapter further explores the corner point method, providing additional insights and practical examples for solving linear programming problems. Simplex Method: The simplex method, a widely used algorithm for solving linear programming problems, is explained in detail, covering the steps involved and highlighting its efficiency. Degeneracy: This section examines the concept of degeneracy in linear programming, discussing scenarios where degeneracy occurs and its impact on the optimization process. Duality: Exploring the duality theory in linear programming, this chapter sheds light on the relationship between the primal and dual problems, offering a deeper understanding of the subject. Dual of L.P.P: This section focuses specifically on the dual problem formulation in linear programming, providing insights into its significance and application in various scenarios. North West Corner Method: Introducing the North West Corner method, this chapter presents an algorithmic approach to solving transportation problems associated with linear programming. Whether you are a student, researcher, or professional in the field of operations research, management science, or optimization, "Linear Programming: A Comprehensive Guide" is an essential reference that will enhance your understanding and proficiency in linear programming techniques.