Applied Mathematics: The Hidden Engine Powering Tomorrow’s Breakthroughs

Author(s): Saif Ali Kheraj

Originally published on Towards AI.

How applied mathematicians solve real-world optimization problems in industry

In the world of operations research and applied mathematics, few algorithms are as elegant and powerful as the simplex method for solving linear programming problems. Whether you are optimizing supply chains, maximizing portfolio returns, or allocating manufacturing resources, understanding the mechanics behind this foundational algorithm provides crucial insight into how mathematical optimization drives business decisions.

The article explores the simplex method’s fundamental role in applied mathematics, detailing its application in solving linear programming issues across various industries. It emphasizes the algorithm’s efficiency in enhancing operational decisions, while also delving into the mathematical principles of optimization it employs. Through examples and case studies, the author highlights its transformative impact on sectors like healthcare and engineering, ultimately showcasing how applied mathematicians leverage this method to drive meaningful change and solve complex real-world problems.

Read the full blog for free on Medium.

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Published via Towards AI