A robust hybrid multi-criteria decision making methodology for contractor evaluation and selection in third-party reverse logistics

Due to green legislations, industries track the used products through reverse logistics contractors. A reverse logistics programme offers significant cost savings in procurement, transportation, disposal and inventory carrying. Since reverse logistics operations and the supply chains they support are considerably more complex than traditional manufacturing supply chains, it can be offered to third party contractors. But availability of more number of contractors make evaluating and selecting the most efficient Reverse Logistics Contractor (RLC) a challenging task and treated as a multi-criteria decision making problem. In this paper, a hybrid method using Analytical Hierarchy Process (AHP) and the Fuzzy Technique for Order Preference by Similarity to Ideal Solutions (TOPSIS) is proposed. AHP is used to obtain the initial weights and Fuzzy TOPSIS is used to get the final ranking. A case study demonstrates the application of the proposed method. Finally sensitivity analysis is carried out to confirm the robustness.     

Integrating Fuzzy C-Means and TOPSIS for performance evaluation: An application and comparative analysis

In this paper we introduce a multi-method multiple criteria approach for evaluating the performance of organizations. Performance analysis may include both strategic and operational performance, as well as financial and other less tangible factors. This paper introduces the use of Fuzzy C-Means and TOPSIS for organizational performance evaluation purposes. Using real company data and balanced scorecard accounting and performance dimensions the methodology is applied and evaluated. The predictive abilities of the technique from an organizational performance evaluation approach are evaluated using this data. One of the results from the illustrative application is that economic performance evaluation is not the best predictor of overall viability of some organizations, especially e-commerce based organizations.     

Robust spatial flood vulnerability assessment for Han River using fuzzy TOPSIS with α-cut level set

This study aims to improve the general flood vulnerability approach using fuzzy TOPSIS based on α-cut level sets which can reduce the uncertainty inherent in even fuzzy multi-criteria decision making process. Since fuzzy TOPSIS leads to a crisp closeness for each alternative, it is frequently argued that fuzzy weights and fuzzy ratings should be in fuzzy relative closeness. Therefore, this study used a modified α-cut level set based fuzzy TOPSIS to develop a spatial flood vulnerability approach for Han River in Korea, considering various uncertainties in weights derivation and crisp data aggregation. Two results from fuzzy TOPSIS and modified fuzzy TOPSIS were compared. Some regions which showed no or small ranking changes have their centro-symmetric distributions, while other regions whose rankings varied dynamically, have biased (anti-symmetric) distributions. It can be concluded that α-cut level set based fuzzy TOPSIS produce more robust prioritization since more uncertainties can be considered. This method can be applied to robust spatial vulnerability or decision making in water resources management.     

A fuzzy AHP-TOPSIS framework for ranking the solutions of Knowledge Management adoption in Supply Chain to overcome its barriers

The aim of this study is to identify and prioritize the solutions of Knowledge Management (KM) adoption in Supply Chain (SC) to overcome its barriers. It helps organizations to concentrate on high rank solutions and develop strategies to implement them on priority. This paper proposes a framework based on fuzzy analytical hierarchy process (AHP) and fuzzy technique for order performance by similarity to ideal solution (TOPSIS) to identify and rank the solutions of KM adoption in SC and overcome its barriers. The AHP is used to determine weights of the barriers as criteria, and fuzzy TOPSIS method is used to obtain final ranking of the solutions of KM adoption in SC. The empirical case study analysis of an Indian hydraulic valve manufacturing organization is conducted to illustrate the use of the proposed framework for ranking the solutions of KM adoption in SC to overcome its barriers. This proposed framework provides a more accurate, effective and systematic decision support tool for stepwise implementation of the solutions of KM adoption in SC to increase its success rate.     

DEM和土地利用分辨率对SWAT水沙模拟效果的影响——以泾河流域为例

DEM和土地利用的数据精度影响水文模型的模拟效果。以泾河流域为对象,选取毛家河、杨家坪和张家山3个水文站作为控制站,分别利用9组不同分辨率的DEM和土地利用数据（分辨率范围均为30～3 000 m）构建了100个SWAT模型,探究输入数据精度对水沙模拟效果的影响,并采用TOPSIS理论方法对模型进行综合评价。研究表明：DEM分辨率会影响流域的边界和河网提取,且流域特征信息会随分辨率的降低而发生丢失;当DEM分辨率低于1 000 m时,需使用SWAT中的Burn in工具,才能完成流域边界与河网的准确提取;HRU的数量随DEM分辨率的下降而减少,而土地利用分辨率对HRU数量的影响不显著;当分辨率变化较大时,DEM对参数敏感性造成的影响要大于土地利用;在构建的毛家河、杨家坪和张家山3个站点的模型中,DEM和土地利用分辨率的最优组合分别为750和300 m、30和90 m以及150和3 000 m。该研究可为流域水沙模型构建与模拟精度提升提供方法与技术参考。     

改进TOPSIS法在甘肃省农村饮水安全评价中的应用

饮水安全是人类健康的基本保障。针对甘肃省农村饮水安全问题,运用层次分析法、熵权法、改进TOPSIS法以及障碍度模型,评价了甘肃省2005、2015以及2020年的农村饮水安全状况,比较了改进TOPSIS法与模糊综合评价模型评价结果的差异,以期建立适用于甘肃省的综合评价指标体系,为农村饮水安全工程建设提供科学参考。结果表明：2005-2020年,甘肃省农村饮水安全水平逐步提升,2020年各地市（州）农村饮水安全水平均已达到基本安全水平以上;甘肃省农村饮水安全工程建设的主要障碍因子为集中供水率和自来水普及率;与模糊综合评价模型相比,改进TOPSIS法的客观性更强,计算过程中的信息损失量小,可以在农村饮水安全评价研究中进一步应用。甘肃省农村饮水安全工程建设已取得较大成效,未来需围绕薄弱环节巩固提高。     

中山市水资源系统动态模拟与敏感性分析EI北大核心CSCD

为满足区域水资源可持续开发与高效利用条件下中山市未来的社会经济发展需求,构建了系统动力学模型,模拟中山市经济社会、水资源供需及水环境的变化趋势,采用了熵权TOPSIS模型进行参数敏感性分析,综合评价不同参数变化对2030年和2040年水质、水量以及经济社会的影响。结果表明:常规发展模式下,中山市水资源供需矛盾逐渐凸显,水环境恶化愈发严重;控制用水量的方案对促进区域可持续发展的作用较为明显,且万元工业(不含火电)增加值用水量的减少产生效果最为显著;不同参数调整方案对水资源系统近期及远期的影响不尽相同,为使水资源管理政策更加适合长远的发展,应重视远期作用明显的参数调整方案。     

污水处理厂PPP项目优选研究

如何在众多污水处理厂PPP项目中挑选出风险低、回报适宜的优质项目不仅是社会资本方关注的重点,也是推动PPP项目顺利开展的关键。从社会资本方的角度出发,建立政府能力及环境、项目特征、项目影响3个方面的较为完善的污水处理厂PPP项目评价体系,采用聚类分析法从类别内、类别间两方面综合计算专家权重,以此修正AHP法确定的指标权重,并结合TOPSIS模型对众多污水处理厂PPP项目进行比较,优选出最适宜投资的项目。通过实例验证,此方法可行、有效,且社会资本方对项目特征、政府能力及环境两方面非常重视。     

不确定视角下改进TOPSIS法的工程评标模型研究

评标质量决定中标者与招标项目的契合程度,但受经验知识和主观判断等影响,定性指标的量化过程易带有主观模糊性,从而影响结果准确度。为减少模糊因素对评标结果的负作用,引入Z-number模糊数识别定性指标的不确定性,依据熵值原理客观确定评标指标及评标专家权重,TOPSIS法集成指标值,构建基于Z-number理论的改进TOPSIS法评标模型。结果表明,提议方法不仅能明晰度量定性指标值本身的模糊程度,还实现了指标值不确定性的针对化削减。同时,在有效避免主观赋权带来的不确定性基础上,该方法也克服了指标间的不可公度性。通过示例分析与敏感性分析验证了模型的实效性与稳定性。     

基于灰色理想解法的模糊多属性决策方法研究

针对方案评估中属性信息的模糊性,提出了一种基于熵权和灰色理想解法的决策方法.该方法先将属性的模糊信息转化为三角模糊数,再利用三角模糊数的性质和信息熵的思想,求出属性的熵权.然后,用灰色理论对传统理想解法进行拓展,将灰色关联度和欧氏距离有机结合构造出一种相似接近度对方案进行评价.相似接近度同时反映了方案与正负理想方案之间的位置和数据曲线的相似性差异,这种方法使其物理意义更加明确.通过算例说明了方法的可行性和有效性.