求解双极Max-Tp方程约束多目标优化问题

Q3 Computer Science International Journal of Advances in Soft Computing and its Applications Pub Date : 2016-11-30 DOI:10.5121/IJSC.2016.7402

Cheng-Kai Hu, Fung-Bao Liu, Cheng-Feng Hu

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引用次数: 8

摘要

研究一类具有极大积组合的双极模糊关系方程组约束下的多目标优化问题。针对这类问题，提出了一种基于与理想解相似度排序的整数优化方法。研究了双极max-Tp方程约束优化问题可行域和最优解的一些关键特征。最后通过一个实例验证了本文的思想。本文首次尝试从整数规划的角度研究双极max-T方程约束多目标优化问题。

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Solving Bipolar Max-Tp Equation Constrained Multi-Objective Optimization Problems

This work considers the multi-objective optimization problem constrained by a system of bipolar fuzzy relational equations with max-product composition. An integer optimization based technique for order of preference by similarity to the ideal solution is proposed for solving such a problem. Some critical features associated with the feasible domain and optimal solutions of the bipolar max-Tp equation constrained optimization problem are studied. An illustrative example verifying the idea of this paper is included. This is the first attempt to study the bipolar max-T equation constrained multi-objective optimization problems from an integer programming viewpoint.

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来源期刊

International Journal of Advances in Soft Computing and its Applications Computer Science-Computer Science Applications

CiteScore

3.30

自引率

0.00%

发文量

期刊介绍： The aim of this journal is to provide a lively forum for the communication of original research papers and timely review articles on Advances in Soft Computing and Its Applications. IJASCA will publish only articles of the highest quality. Submissions will be evaluated on their originality and significance. IJASCA invites submissions in all areas of Soft Computing and Its Applications. The scope of the journal includes, but is not limited to: √ Soft Computing Fundamental and Optimization √ Soft Computing for Big Data Era √ GPU Computing for Machine Learning √ Soft Computing Modeling for Perception and Spiritual Intelligence √ Soft Computing and Agents Technology √ Soft Computing in Computer Graphics √ Soft Computing and Pattern Recognition √ Soft Computing in Biomimetic Pattern Recognition √ Data mining for Social Network Data √ Spatial Data Mining & Information Retrieval √ Intelligent Software Agent Systems and Architectures √ Advanced Soft Computing and Multi-Objective Evolutionary Computation √ Perception-Based Intelligent Decision Systems √ Spiritual-Based Intelligent Systems √ Soft Computing in Industry ApplicationsOther issues related to the Advances of Soft Computing in various applications.