matlab基本知识分析与心得（萌说新语MATLAB学习3-2）

MATLAB学习——VIKOR方法步骤与代码实现(2)

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大家好，本周小编为大家带来的是MATLAB的VIKOR方法步骤与代码实现，为方便大家进行学习理解，小编选取论文《基于信息熵－VIKOR模型的4PL供应商优选决策研究》进行综合讲解帮助大家进行学习。

上一阶段我们求取了群体效用值与个体遗憾值，我们求取结果之后，需要在此基础上计算决策指标Qi的值，指标值越小方案越优。

其公式为:

Hello everyone, this week, the editor brings you the VIKOR method steps and code implementation of MATLAB. In order to facilitate everyone's learning and understanding, the editor selects the paper "Research on 4PL Supplier Selection Decision Based on Information Entropy-VIKOR Model" for synthesis Explain to help everyone learn.

In the previous stage, we obtained the group utility value and the individual regret value. After we obtained the results, we need to calculate the value of the decision-making index Qi on this basis. The smaller the index value, the better the plan.

Its formula is:

其中

V表示为决策机制系数，如果V<0.5，则表示根据最大化群体效应决策机制决策；如果V>0.5，则表示根据最小化个体遗憾值的决策机制决策；如果V=0.5，则表示根据协商达成最大群体效应和最小个体遗憾值同等重要的决策机制进行决策。最终，可以得到各方案的Qi值，而Qi值越小越好，将进行升序排列得到各方案的排序结果。而本次参照论文中根据丁日佳等(2016)的研究，为将群体效用最大化和负面影响最小化，此处采用均衡方式，取v=0.5。

V is the coefficient of the decision-making mechanism. If V<0.5, it means that the decision is made according to the decision-making mechanism that maximizes the group effect; if V>0.5, it means that the decision is made according to the decision-making mechanism that minimizes the individual regret value; if V=0.5, it means that the decision is based on negotiation A decision-making mechanism that achieves the largest group effect and the smallest individual regret value is equally important to make decisions. Finally, the Qi value of each scheme can be obtained, and the smaller the Qi value, the better, and the sorting result of each scheme will be obtained by sorting in ascending order. In this reference paper, according to the research of Ding Rijia et al. (2016), in order to maximize the group utility and minimize the negative impact, the equilibrium method is adopted here, and v=0.5.

此处在MATLAB代码中的表现形式为：

Best_S=min(S);

Worst_S=max(S);

Best_R=min(R);

Worst_R=max(R);

v=0.5

% v is decision mechanism coefficient.

Q=[ ];

% Q is the evaluation index.

for i=[1:Origin_Matrix_Row]

Q(end 1)=v*(S(i)-Best_S)/(Worst_S-Best_S) (1-v)*(R(i)-Best_R)/(Worst_R-Best_R);

end

display(Q)

之后按照Qi、Si、Ｒi分别从小到大排序，每个序列中排在前面的方案优于后面的。根据丁日佳等(2016)的研究，在全部满足以下两个条件时，按照Qj值大小排列。

条件1:可接受的优势阀值条件:Q″－Q'≥1/(n－1)则Q'是排序中的最优评价对象，Q″是排序中次优评价对象。

条件2:可接受的决策可靠性条件:排序第一的方案的S值或Ｒ值比排序第二方案的S值或Ｒ值小。当有数个方案时，依次比较排序第一、第二、第三等方案之间是否符合两个条件。评判准则是当排序第一的方案和排序第二的方案同时满足两个条件时，接受排序第一的方案为最优方案;若条件2不满足，则同时接受两个方案为最优方案;若条件1不满足，则同时接受不满足条件1的所有方案为最优方案。

Then, according to Qi, Si and Ri, they are sorted from small to large, and the schemes ranked in the front in each sequence are better than those in the back. According to the research of Ding Rijia et al. (2016), when all the following two conditions are met, they are arranged according to the value of Q.

Condition 1: Acceptable advantage threshold condition: Q"-Q'≥1/(n-1), then Q' is the optimal evaluation object in the sorting, and Q" is the second-best evaluation object in the sorting.

Condition 2: Acceptable decision reliability condition: The S value or R value of the first-ranked scheme is smaller than the S-value or R-value of the second-ranked scheme. When there are several schemes, compare and sort the first, second, and third schemes in order to see if the two conditions are met. The judging criterion is that when the first-ranked scheme and the second-ranked scheme satisfy two conditions at the same time, the first-ranked scheme is accepted as the optimal scheme; if the condition 2 is not satisfied, both the two schemes are accepted as the optimal scheme; If Condition 1 is not satisfied, then accept all the schemes that do not satisfy Condition 1 at the same time as the optimal scheme.

此处MATLAB中的代码表现为：

Result_1='The best plan is A';

Result_2=' and';

Result_3=' A';

Result_4='.';

Q_1st=min(Q)

Q_2nd=min(Q(find(Q-min(Q))))

if S(find(Q==Q_1st))<s(find(q==q_2nd))< span="">

if R(find(Q==Q_1st))<r(find(q==q_2nd))< span="">

disp('Condition 2 is satisfied.')

Result=[Result_1,num2str(find(Q==min(Q))),Result_4];

end

elseif Q_2nd-Q_1st>(1/length(Q)-1)

disp('Condition 2 is not satisfied.')

disp('Condition 1 is not satisfied.')

Result=[Result_1,num2str(find(Q==min(Q))),Result_2,Result_3,...

num2str(find(Q==min(Q(find(Q-min(Q)))))),Result_4];

else disp('Condition 2 is not satisfied.')

disp('Condition 1 is satisfied.')

Result=[Result_1,num2str(find(Q==min(Q))),Result_4];

end

disp(Result)

SPRING

FESTIVAL

最后作者对4PL供应商选择结果分析。依据改进的VIKOR模型对4PL供应商的选择排序结果为P3＞P2＞P1。因此，建议选择P3作为最优4PL供应商。通过与张滢的优选结果P3＞P1＞P2对比可以发现，最优方案具有一致性，P2与P1的选择顺序发生改变主要可能是本文中加入供应链风险管理评价指标及对原文部分评价指标进行改进所致。研究结果表明，4PL供应商中P3供应商具有较强的稳定性和优越性，在供应链整合协作能力、供应链风险管理能力、市场竞争力和管理组织能力方面均表现出非常强的竞争优势。研究结果表明信息熵－VIKOR模型在4PL供应商选择中具有较好的稳健性和适用性。

Finally, the author analyzes the results of 4PL supplier selection. According to the improved VIKOR model, the selection ranking result of 4PL suppliers is P3>P2>P1. Therefore, it is recommended to choose P3 as the optimal 4PL provider. By comparing with Zhang Ying's optimization result P3>P1>P2, it can be found that the optimal scheme is consistent, and the change of the selection order of P2 and P1 may be mainly due to the addition of supply chain risk management evaluation indicators in this paper and the evaluation of some of the original text evaluation indicators. due to improvement. The research results show that among 4PL suppliers, P3 suppliers have strong stability and superiority, and show very strong competitive advantages in supply chain integration and collaboration ability, supply chain risk management ability, market competitiveness and management organization ability. . The research results show that the information entropy-VIKOR model has good robustness and applicability in 4PL supplier selection.

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