Optimization Algorithms for Multi-Criteria Decision-Making

Dear Colleagues,

Multi-criteria decision making (MCDM) techniques have been successfully applied to complex decision-making problems in economics, finance, logistics, environmental restoration, health, and industrial organization. MCDM is a methodical, quantitative way to handle situations involving multiple choices and competing criteria. Many analytical approaches have been used to assess trade-offs; consider multiple scientific, political, economic, ecological, and social factors; and decrease any conflicts in an optimum framework. MCDM is becoming increasingly common for academics in various big data application sectors to uncover unique ways to create decision-support systems that incorporate numerous criteria with the integration of machine learning and artificial intelligence (ML/AI). MCDM approaches are considered established methods to aid decision-makers in choosing suitable judgments, and their applications are rising in popularity in many industries, including company management, logistics, supply chains, energy, urban planning, waste management, etc. MCDM methods are used in many engineering applications to determine or choose the best alternative from a collection of options. The aim of this Special Issue is to propose and develop computational-intelligence-based algorithms and/or machine learning and artificial-intelligence-based methods to solve problems that involve multiple criteria and alternatives and may involve many decision makers.

Dr. Mohamed Abdel-Basset
Dr. Karam Sallam
Guest Editors

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