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The Intersection of Machine Learning with Forecasting and Optimisation: Theory and Applications

In: Forecasting with Artificial Intelligence

Author

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  • Mahdi Abolghasemi

    (The University of Queensland)

Abstract

Forecasting and optimisation are two major fields of operations research that are utilised to deal with uncertainties and to make the best decisions. These methods are widely used in academia and practice and have contributed to each other growth in several ways. These methods can be used together to solve various problems in transportation, scheduling, production planning, and energy where both forecasting and optimisation are needed. However, the nature of the relationship between these two methods and how they can be integrated for better performance have not been explored or understood enough. We advocate the integration of these two methods and explore several problems that require both forecasting and optimisation. I will investigate some of the methodologies that lie at the intersection of machine learning with forecasting and optimisation to address real-world problems. I will provide several research directions and use cases for researchersResearchers and practitioners interested to explore this interesting arena.

Suggested Citation

  • Mahdi Abolghasemi, 2023. "The Intersection of Machine Learning with Forecasting and Optimisation: Theory and Applications," Palgrave Advances in Economics of Innovation and Technology, in: Mohsen Hamoudia & Spyros Makridakis & Evangelos Spiliotis (ed.), Forecasting with Artificial Intelligence, chapter 0, pages 313-339, Palgrave Macmillan.
    • Handle: RePEc:pal:paiecp:978-3-031-35879-1_12
    DOI: 10.1007/978-3-031-35879-1_12
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