Chapter 10. Operations Research

Many scientists owe their greatness not to their skill in solving problems but to their wisdom in choosing them.

E. Bright Wilson (1908–1992), American chemist

In this chapter, we explore the integration of AI into the field of operations research, leveraging the best of both worlds for more efficient and more informed decision making. Although this introductory statement sounds like an ad, it is precisely what operations research is all about. Advances in machine learning can only help move the field forward.

Operations research is one of the most attractive and stimulating areas of applied mathematics. It is the science of balancing different needs and available resources in the most time- and cost-efficient ways. Many problems in operations research reduce to searching for an optimal point, the holy grail, at which everything functions smoothly and efficiently: no backups, no interruptions to timely services, no waste, balanced costs, and good revenues for everyone involved. A lot of applications never find the holy grail, but many operations research methods allow us to come very close, at least for the simplified models of the complex reality. Constrained mathematical optimization penetrates every industry, every network, and every aspect of our lives. Done properly, we enjoy its benefits; done improperly, we suffer its impact: global and local economies are still experiencing the ramifications of COVID-19, the war on Ukraine, and the interruptions ...

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