A Fuzzy-Analytical Hierarchy Model for Solid Waste Management Location in South-West Nigeria

Rapid urbanization and industrialization have led to the generation of considerable quantities of municipal and industrial wastes. These often result in spread of diseases, contaminations of water body and pollution of soil, thus the selection of a good landfill location is a multiple criteria problem. This work developed fuzzy analytical hierarchical model as a decision support system. The fuzzy based hierarchical model first converted the perception into triangular fuzzy numbers and used the concept of extent value analysis to obtain the significance of each of the criterion, sub criterion and the decision alternative. The developed model was applied to a landfill location problem of Ibadan, Oyo state. Five main criteria, sixteen sub criteria and three decision alternatives were considered via; Eleyele, Moniya and Iyana Ofa. The performances of Eleyele, Moniya, and Iyana Ofa through fuzzy based hierarchical model are 0.314, 0.324 and 0.385 respectively. The decision making technique indicates that, Iyana Ofa which has the highest performance should be selected for landfill location in Ibadan. Fuzzy analytic hierarchic process as a decision making technique is robust and can reduce imprecision in the mapping of perceptions of decision makers into numerical evaluation, thus making fuzzy based hierarchical model accurate, stable and reliable. Keywords: China insurance industry, Foreign fund, Challeng

About the Multi Criteria Ranging Problem in the Fuzzy Environment

Decision making and technical decision analysis demand computer-aided techniques and therefore more and more support by formal techniques. In recent years fuzzy decision analysis and related techniques gained importance as an efficient method for planning and optimization applications in fields like production planning, financial and economical modeling and forecasting or classification. It is also known, that the hierarchical modeling of the situation is one of the most popular modeling method. It is shown, how to use the fuzzy hierarchical model in complex with other methods of Multiple Criteria Decision Making. We propose a novel approach to overcome the inherent limitations of Hierarchical Methods by exploiting multiple criteria decision making

A fuzzy hierarchical multiple criteria group decision support system - Decider - and its applications

Decider is a Fuzzy Hierarchical Multiple Criteria Group Decision Support System (FHMC-GDSS) designed for dealing with subjective, in particular linguistic, information and objective information simultaneously to support group decision making particularly on evaluation. In this chapter, the fuzzy aggregation decision model, functions and structure of Decider are introduced. The ideas to resolve decision and evaluation problems we have faced in the development and application of Decider are presented. Two real applications of the Decider system are briefly illustrated. Finally, we discuss our further research in this area. © 2011 Springer-Verlag Berlin Heidelberg

Supplier Selection with Fuzzy TOPSIS

For businesses, carrying out their activities successfully is directly related to the suppliers’ efficiency as well as their own performances. Properly selected suppliers make a significant contribution to the competition capacity of enterprises. Therefore, selecting proper suppliers is regarded as a multiple criteria decision making (MCDM) problem, which includes many qualitative and quantitative factors in the process.In this study, a supplier selection model has been developed in order to help executives with proper supplier selection. In this model, Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) method, which is an MCDM method, was used with positive trapezoidal fuzzy numbers. The decision structure and the criteria used in decision support model have been determined based on the literature review. The result of the model demonstrated that all the suppliers evaluated in the study are suitable enough to work with, but the supplier B deserves the first place. Keywords: Fuzzy TOPSIS, Multiple-Criteria Decision Making, Supplier Selection.

Multicriteria Decision Making (MCDM) dengan Choquet Integral untuk Membantu Pemilihan Pembelian Mobil

ABSTRAKSI: Konsumen dalam memilih mobil yang sesuai dengan kebutuhan serta kemampuan keuangannya terkadang menemukan kendala. Terutama bagi pelanggan yang tidak begitu familiar dengan industri otomotif. Mereka cenderung membutuhkan seorang konsultan atau seseorang yang mengetahui mobil, dalam menentukan mobil apa yang dapat mereka dapatkan.Di dalam tugas akhir ini, dipergunakan Multicriteria Decision Making (MCDM) sebagai alat bantu dalam menentukan keputusan. Multicriteria Decision Making (MCDM) adalah suatu metode pengambilan keputusan untuk menetapkan alternatif terbaik dari sejumlah alternatif berdasarkan beberapa kriteria tertentu[11]. Model yang dipakai untuk mendukung pengambilan keputusan ini adalah fuzzy model dan membantu dalam menentukan bobot dari setiap kriteria dipergunakan Choquet Integral yang diintegrasikan pada fuzzy measure [3][6][12]. Hal ini dapat dilakukan karena salah satu properti karakteristik Choquet integral yang monotonicity sehingga dapat digunakan untuk membantu dalam pengambilan keputusan yang tidak pasti. Dari bobot yang telah dihasilkan, dibuat rank-ordering [1].Kata Kunci : Multicriteria Decision Making (MCDM), Fuzzy model, FuzzyABSTRACT: Sometimes customer having difficulties in picking car based on their needs and financial. Especially for customer whose not familiar with automotive industry,. They need a consultant or someone whose know car to decide what kind of car that they can get.In this final project, is implemented using Multicriteria Decision Making (MCDM) as a tool to determine a decision. Multicriteria Decision Making (MCDM) is a method decision support to decide the best alternative from sum of alternative for certain criteria[11]. Model that being used to support decision is fuzzy model and to help in decide the weighted sum of every criteria used Choquet integral integrated in fuzzy measure [3][6][12]. It can be done because the one characteristic property of Choquet integral is monotonicity therefore it can be used to support in decided decision that uncertain. From the result of weighted sum, made rank ordering[1]. Keyword : In this final project, is implemented using Multicriteria Decision Making (MCDM) as a tool to determine a decision. Multicriteria Decision Making (MCDM) is a method decision support to decide the best alternative from sum of alternative for certain criteria[11]. Model that being used to support decision is fuzzy model and to help in decide the weighted sum of every criteria used Choquet integral integrated in fuzzy measure [3][6][12]. It can be done because the one characteristic property of Choquet integral is monotonicity therefore it can be used to support in decided decision that uncertain. From the result of weighted sum, made rank ordering[1].Keyword: In this final project, is implemented using Multicriteria Decision Makin

Power distribution system planning evaluation by a fuzzy multi-criteria group decision support system

The evaluation of solutions is an important phase in power distribution system planning (PDSP) which allows issues such as quality of supply, cost, social service and environmental implications to be considered and usually involves the judgments of a group of experts. The planning problem is thus suitable for the multi-criteria group decision-making (MCGDM) method. The evaluation process and evaluation criteria often involve uncertainties incorporated in quantitative analysis with crisp values and qualitative judgments with linguistic terms; therefore, fuzzy sets techniques are applied in this study. This paper proposes a fuzzy multi-criteria group decision-making (FMCGDM) method for PDSP evaluation and applies a fuzzy multi-criteria group decision support system (FMCGDSS) to support the evaluation task. We introduce a PDSP evaluation model, which has evaluation criteria within three levels, based on the characteristics of a power distribution system. A case-based example is performed on a test distribution network and demonstrates how all the problems in a PDSP evaluation are addressed using FMCGDSS. The results are acceptable to expert evaluators. © 2010 Taylor & Francis Group, LLC

Reliability information to support decision making for e-Government projects

E-government implementations in developing countries still face difficulties, leading to a large failure ratio. This paper proposed an exponential-related function adopted in an intuitionistic Fuzzy TOPSIS model for improving the understanding of failure and for building appropriate reliability knowledge to support decision making for e-government projects. The new method which is simple and straightforward have been successfully applied by virtue of numerical case studies for detecting failures, which in turn has provided information for building reliability knowledge to support decision making process. The method has been compared successfully with some similar computational approach in literature

Development of Fuzzy Multi Criteria Decision Making Method for Selection of Optimum Maintenance Alternative

An optimal maintenance strategy is a key support to production in the manufacturing industry. This paper present a fuzzy approach based on Multi-Criteria Decision-Making (MCDM) methodology for selecting the optimal maintenance alternative. In the present work the criticality of each equipment is achieved by ranking (based on production loss).It is very difficult to quantify the qualitative factors in exact numerical value. These factors can be expressed in the linguistics terms which can be translated into mathematical measures by using fuzzy sets & system theory. The study problem to develop a fuzzy decision approach to rank the suitable maintenance alternative. The objective of this paper is to propose fuzzy frame work based on fuzzy number theory to solve optimal maintenance alternative which includes decision criteria analysis, weight assessment & decision model development. The approach can aid formulating a cost-effective maintenance strategy for a manufacturing plant

Three-way Imbalanced Learning based on Fuzzy Twin SVM

Three-way decision (3WD) is a powerful tool for granular computing to deal with uncertain data, commonly used in information systems, decision-making, and medical care. Three-way decision gets much research in traditional rough set models. However, three-way decision is rarely combined with the currently popular field of machine learning to expand its research. In this paper, three-way decision is connected with SVM, a standard binary classification model in machine learning, for solving imbalanced classification problems that SVM needs to improve. A new three-way fuzzy membership function and a new fuzzy twin support vector machine with three-way membership (TWFTSVM) are proposed. The new three-way fuzzy membership function is defined to increase the certainty of uncertain data in both input space and feature space, which assigns higher fuzzy membership to minority samples compared with majority samples. To evaluate the effectiveness of the proposed model, comparative experiments are designed for forty-seven different datasets with varying imbalance ratios. In addition, datasets with different imbalance ratios are derived from the same dataset to further assess the proposed model's performance. The results show that the proposed model significantly outperforms other traditional SVM-based methods