Mathematical Optimization is a Versatile Problem-solving Technology- Know Why!

Mathematical Optimization is a Powerful and Versatile Problem-solving Technology

MO or mathematical optimization is an incredibly powerful AI technology. It is well-renowned for helping companies dramatically improve their resource utilization, operational efficiency, and overall profitability. MO operation technologies like linear programming and mixed-integer linear programming have been applied in innumerable business areas. They have empowered companies across multiple industries to instantly solve complex real-world problems, make informed business decisions that enhance operational efficiency, and accomplish significant cost-savings and revenue growth.

There are numerous reputed cases of mathematical optimization that have delivered billions of dollars in cost savings and revenue growth for leading companies. These include financial services, telecommunications, electric power, manufacturing, and logistics.

However, every day, we get to know all about new cutting-edge applications that we have never heard of or even imagined were possible. It encompasses everything from urban parking optimization to food delivery dispatch, earthquake modeling to subscription box office optimization, scaffolding design optimization to energy asset modeling, and many more. The possibilities are endless.

This blog is for all the newbies out there who have a vague to no idea of mathematical optimization. How it can impact organizations’ operations and influence future decisions! Stick around to understand how mathematical optimization is such a powerful and versatile AI problem-solving technology.

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Mathematical Optimization: A Quick Overview

Before we delve deep to understand the crucial uses of mathematical optimization are used in the modern-day world. Let’s first comprehend what mathematical optimization truly is –

Mathematical optimization is a brilliant collection of methodologies and exemplary tools that finds the best solution to a mathematical problem subject to a set of constraints. It is the process of maximizing or minimizing an objective function by finding the best available values across a set of inputs.

Dr. Ed Rothberg, Co-Founder, and CEO of Gurobi, when asked about MO, responded saying, “Mathematical optimization helps you make smarter choices about how to use limited resources to produce the best possible business outcome. It starts with a mathematical model of some aspects of your business you can think of it as a ‘digital twin’. The model captures the resources that are require for your business process, the constraints that must be satisfied, and your objectives. The model captures the position of all practical solutions. A MO solver next utilizes this series of sophisticated algorithms to neaten through all probable solutions to get the best.”

A business possessing resource constraints can make use of MO. To find the most effective ways of using and deploying those resources. The objective becomes maximizing operational efficiency and unlocking new business opportunities.

3 Crucial Reasons Mathematical Optimization Is a Versatile and Powerful AI Technology

  • The Broad Application of Mathematical Optimization Solver

In the words of a reputed math problem solver around the world. A MO solver functions as a black box for most users. Although they can use the outputs of the technology, they have little to no understandings of its inner working. However, they don’t really need to. They need to simply integrate the solver into their applications and then let it automatically crunch their data. Further, they can crank out optimal solutions to their business problems.

Imagine a solver as being like an electric motor that can be inserted into so many different things. Such as household appliances, ships, power tools, cars, etc. used to make them run. As the uses of the solver have increased over the years. The performance of the technology has improved- and this phenomenon continues to date. Nevertheless, inside the black box remains a remarkable collection of the world’s most sophisticated, state-of-the-art mathematical algorithms.

The diverse range of applicability of the black-box solver helps in making mathematical optimization. For an AI technology with far-reaching and enduring impact in our world today.

  • The Flexibility of Mathematical Optimization Models

The application of mathematical optimization has two primary components- the solver explains the section above. Also, a mathematical model which encompasses real-world business problems.

Although solver is standard off-the-self-software, the mock-up is a thorough and vastly advanced arithmetical depiction of your company matter. The huge flexibility of the model offers you the ability to captivate complex, mission-critical business problems in mathematical terms. It can also be used to generate an optimal solution to those business problems.

The robust modeling capability is the main reason why MO remains such a versatile and pivotal technology for businesses today. Regardless of how challenging or complex your business problem is! Hence, it can be explained as a mathematical model, it can almost be solved through the use of mathematical optimization.

  • The Ability To Make Optimal Decisions Based On The Latest Available Data

As you know, data is the lifeblood of every AI technology. There are certain AI tools like machine learning that rely completely on historical data to make other predictions. On the contrary, other tools like MO leverage the latest available data and models of the present-day business environment to facilitate and automate decision-making.

The value of your business data can be easily reveal with the use of mathematical optimization to generate solutions to real-world business problems. Also, it helps in overcoming all the obstacles and make sound optimal business decisions.

The Examples of Mathematical Optimization

In the modern-day, mathematical optimization is use by reputed organizations like Uber, Walmart, Microsoft, FedEx, the National Football League, and Air France. They have made use of MO to accomplish huge financial and operational benefits. Further, the process has saved billions of dollars and supported revenue growth for renowned businesses around the world.

Apart from that, we have listed certain remarkable examples that demonstrate ways organizations are presently using MO-

  • Sports Scheduling– NFL uses MO to predict the best possible leaguing schedules.
  • Finance- Mathematical optimization is use by betterment to select the best mix of assets to maximize after-tax returns and minimize the risk hugely.
  • Government- The FCC uses MO to create a two-sided spectrum auction like selling the rights for transmitting signals over specific bands.
  • Logistics- FedEx saves fortunes by mathematically optimizing the routes of packages moving through their shipping network.
  • Manufacturing- SAP uses mathematical optimization to schedule the manufacturing of goods in their factories with minimal waste.
  • Electrical Power Distribution- The New York ISO also makes use of MO to select the most cost-effective methods to provide electricity.

Final Words,

The era of AI is upon us. According to Gartner, by 2024, 75% of enterprises will have operationalized AI. So, the question arises: Which technologies will remain relevant?

The reasons listed above strongly make us feel that MO will continue to be a remarkable tool. It will be utilize in an ever-expanding array of applications by different companies to address their most challenging and significant business problems to make optimal decisions.

Undoubtedly, the opportunities for mathematical optimization across innumerable industries are virtually limitless. In the upcoming years, users in the business world will continue to develop and deploy new innovative applications that will leave us spellbound with groundbreaking cases.

Do you think there are any other reasons for which mathematical optimization can be consider an incredibly powerful and versatile problem-solving technology?


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