Hybrid Intelligent Algorithms and Intelligent Computing for Practical Decision Making in Business and Industry

Dear Colleagues,

As decision-making processes grow in complexity, the role of informed decision making facilitated by hybrid intelligent algorithms and artificial intelligence becomes increasingly crucial across business and industrial applications. These algorithms and methods serve as essential tools, enabling users to explore intricate scenarios by employing a variety of approaches, encompassing machine learning methods as well as optimization techniques such as metaheuristics, genetic algorithms, simheuristics (combination of simulation and metaheuristics), and learnheuristics (combination of machine learning and metaheuristics). Their applications extend across diverse fields, including transportation and logistics, energy, smart cities, finance and insurance, production and manufacturing, healthcare systems, telecommunication networks, and sustainable development initiatives, among others.

The demand for innovative algorithms that enhance intelligent computing systems for practical decision making is evident. In collaboration with the Decision Science Alliance (https://decisionsciencealliance.org/), this Special Issue offers a platform for researchers and practitioners to exchange novel ideas and advancements in this critical area. Topics of interest cover a broad spectrum of algorithms, spanning machine learning methods, optimization techniques, and their applications in intelligent computing systems across various business and industrial contexts.

Prof. Dr. Angel A. Juan
Dr. David Lopez
Dr. Davide Mezzogori
Dr. Teresa Murino
Guest Editors

Manuscript Submission Information

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