Constrained Optimization for Better Business Decisions

How quantum methods will help businesses consider more variables to make better decisions

We are constrained in all aspects of life – time, money, and even health. These constraints drive our decisions and actions every day.

Economic business decisions have constraints as well – volume, labor, time, and cost, along with minimization and maximization for desired outcomes.

If a company doesn’t possess the analytic tools to process large volumes of data, constrained optimization isn’t being used to make better decisions. There are several reasons why constrained optimization isn’t used currently:

  1. Classical computers can’t handle the volume of data we are seeing.
  2. Classical software isn’t designed to compute large variable problems with specific discrete constraints and objectives.
  3. Classical computations can only deliver one result, not a range of possible outcomes that may be more optimal.

This is where quantum computing rules in the world of data and data-driven decision-making. It allows for a three-dimensional state – variables, objectives, and constraints are represented.

The result is a far better representation of real-world complexities and nuances. This could be useful in manufacturing supply chains, retail, and logistics.

Quantum computers aren’t quite ready yet but there are new powerful ways to conduct constrained optimization on conventional computers using quantum methods.

Sources: Supply Chain Management Review, Quantum Computing Inc.

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