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A combinatorial optimization problem is trying to find out the value (combination) of variables that optimizes an index (value) from among many options under various constraints.

With the outbreak of COVID-19, we used an annealing machine to create shifts for our researchers under constraints that took into account the newly created risks of infection.

Reinsurance is critical against natural disaster risks that have increased in recent years. We have used an annealing machine to formulate a reinsurance portfolio utilizing the vast amount of data collected by insurance companies.

In chapter 3, we will cover the knowledge related to the criteria necessary for applying annealing machines to real-world problems.

With the Fitness diagnostic tool, you can confirm whether the optimization examples or problems you are familiar with are actually compatible with an annealing machine.