摘要
为改进TOPSIS法,分别以方案点靠近理想点和远离负理想点为目标,构建非线性规划模型。运用实码加速遗传算法(RAGA)进行求解,可较方便地获得兼具决策方法适应性和决策者偏好的指标综合权重。由此,基于RAGA的改进TOPSIS法可在一定程度上克服传统TOPSIS法的不足。应用实例证明了该方法的可行性和有效性。
In order to improve the TOPSIS method,respectively taking the feasible scheme close to ideal solution and far from negative ideal solution as the goal,two nonlinear programming models are established in this paper.Using real coded accelerating genetic algorithm（RAGA）,two models above are solved.And then,the combination weight of index both having the adaptability to the decision-making method and the decision-maker＇s preference information is obtained conveniently.Therefore,the draw back of the traditional TOPSIS method is overcome to a certain extent by the improved TOPSIS method based RAGA.Through a specific example,it is proved that the proposed method is feasible and effective.
出处
《计算机工程与应用》
CSCD
北大核心
2009年第17期235-237,240,共4页
Computer Engineering and Applications
基金
国家自然科学基金(No.70671017)~~
关键词
多属性决策
TOPSIS法
非线性规划
实码加速遗传算法
综合赋权
multi-attribute decision-making
TOPSIS method
nonlinear programming
real coded accelerating genetic algorithm
combination weight
