A New Approach to Multi-objective Programming Based on Satisfied Degree under Fuzzy Environment

Jing-Duo Jie, Fachao Li, Chenxia Jin
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Abstract

Fuzziness is a common uncertainty who exists widespread in decision process and how to process fuzziness is a widespread context in academic and application fields. For the multi-objective programming under fuzzy environment, this paper firstly analyze the essential characteristics of fuzzy objectives. Then fuzzy objectives are divided into three kinds and represent by fuzzy number by introducing deviation parameter α . Then, regarding membership of fuzzy number as the satisfied degree, we establish the multi-objective programming based on satisfied degree (denotes as MP-SD) and a new solving strategy based on MP-SD is further given. Finally, we illustrate the validity of MPSD through a case. The analytical results show that the proposed approach is effective in fuzzy decision environment and provide rich decision theories for integrated multi-objective programming problems in artificial intelligence and resource management and so on.
模糊环境下基于满意度的多目标规划新方法
模糊是一种普遍存在于决策过程中的不确定性,如何处理模糊是学术界和应用领域广泛关注的问题。针对模糊环境下的多目标规划问题,首先分析了模糊目标的基本特征。然后通过引入偏差参数α,将模糊目标分为三类,用模糊数表示。然后,以模糊数的隶属度为满意程度,建立了基于满意程度的多目标规划(表示为MP-SD),并给出了一种新的基于MP-SD的求解策略。最后,通过一个案例说明了MPSD的有效性。分析结果表明,该方法在模糊决策环境下是有效的,为人工智能和资源管理等领域的集成多目标规划问题提供了丰富的决策理论。
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