广东工业大学学报2025，Vol.42Issue(4)：8-19,12.DOI:10.12052/gdutxb.250114
基于可拓学的多目标开放性问题求解方法研究
The Method for Solving Multiple Criteria Ill-defined Problems Based on Extenics
摘要
Abstract
With the rapid advancement of the Internet,the Internet of Things,and artificial intelligence technologies,information is experiencing exponential growth.The widespread adoption of data services has significantly increased the complexity,uncertainty,and dynamism of internal and external environments.This paper builds upon the solution methods for Single-goal Ill-defined Problems,and defines Multiple Criteria Ill-defined Problems as those in which the objectives and domains are relatively well-defined,but due to uncertain or insufficient environmental resources,conditional boundaries,or constraints,conflicts arise among the goals,making it difficult or impossible to achieve them simultaneously.To address such challenges,an initial extension model construction method is proposed for Multiple Criteria Ill-defined Problems.By integrating extensible analysis methods,extension transformation methods,and superiority evaluation methods,the approach seeks to derive optimal or near-optimal strategies for achieving the intended goals.A general procedural framework for solving Multiple Criteria Ill-defined Problems is developed,along with a flowchart that outlines the key steps.Finally,a case study is presented to demonstrate the feasibility and effectiveness of the proposed method.The solution approach is characterized by formalization,modeling,and quantification.It provides a foundational methodology for the intelligent resolution of ill-defined problems,and further extends the application scope of Extenics in addressing goal conflicts and complex decision-making scenarios.关键词
可拓学/多目标开放性问题/可拓模型/拓展分析/可拓变换Key words
Extenics/multiple criteria ill-defined problems/extension models/extensible analysis/extension transformation分类
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曾佳子,梁镇城,李兴森..基于可拓学的多目标开放性问题求解方法研究[J].广东工业大学学报,2025,42(4):8-19,12.基金项目
国家自然科学基金资助项目(72071049) （72071049）
广东省自然科学基金资助项目(2024A1515011324) （2024A1515011324）
