Kaiying Kang, Jialiang Xie, Xiaohui Liu, Honghui Wang
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Overview of the application of intelligent optimization algorithms in multi-attribute group decision making
Intelligent Optimization Algorithms (IOAs) have great potential in solving multi-attribute group decision-making (MAGDM) problems. These problems have gradually become a research hotspot in the field of intelligent decision-making due to their advantages of high decision-making accuracy, versatility, and objective evaluation. This study provides a detailed analysis of the challenges in the MAGDM process and evaluates the feasibility of applying IOAs in this context. Specifically, we study the application of IOAs in the MAGDM process and discuss the advantages and limitations across various application scenarios, including the applications of granulating linguistic information, adjusting decision information, optimizing weights, and aggregating decision information. In addition, the development prospects and challenges of IOAs integration with MAGDM are summarized.
期刊介绍:
With a focus on research in artificial intelligence and neural networks, this journal addresses issues involving solutions of real-life manufacturing, defense, management, government and industrial problems which are too complex to be solved through conventional approaches and require the simulation of intelligent thought processes, heuristics, applications of knowledge, and distributed and parallel processing. The integration of these multiple approaches in solving complex problems is of particular importance.
The journal presents new and original research and technological developments, addressing real and complex issues applicable to difficult problems. It provides a medium for exchanging scientific research and technological achievements accomplished by the international community.