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In this article, we introduce a method for schedule optimization using constraint programming with OR‑Tools, an open‑source optimization solver developed by Google. As a toy model, we consider the scenario of “caring for newborn triplets.” With limited resources (Dad, Mom, and a babysitter), how should multiple tasks be allocated to reduce the parents’ burden—especially sleep deprivation?

This column is filled with hints for advancing issue clarification and requirement definition, so if you're unsure where to start or how to articulate your thoughts as you progress in your study of mathematical optimization, please take a moment to read it.

In this column, I would like to introduce the know-how for applying mathematical optimization technology, including CMOS annealing, to issues that require human decision-making.

Both machine learning, which is often used in AI, and annealing machines, which perform combinatorial optimization, are computers that perform difficult processing on behalf of humans.