Simulation-based evaluation of defuzzification-based approaches to fuzzy multi-attribute decision making

This paper presents a simulation-based study to evaluate the performance of 12 defuzzification-based approaches for solving the general fuzzy multiattribute decision-making (MADM) problem requiring cardinal ranking of decision alternatives. These approaches are generated based on six defuzzification methods in conjunction with the simple additive weighting (SAW) method and the technique for order preference by similarity to the ideal solution method. The consistency and effectiveness of these approaches are examined in terms of four new objective performance measures, which are based on five evaluation indexes. The Simulation result shows that the approaches, which are capable of using all the available information on fuzzy numbers, effectively in the defuzzification process, produce more consistent ranking outcomes. In particular, the SAW method with the degree of dominance defuzzification is proved to be the overall best performed approach, which is, followed by the SAW method with the area center defuzzification. These findings are of practical significance in real-world settings where the selection of the defuzzification-based approaches is required in solving the general fuzzy MADM problems under specific decision contexts

Aggregation Methods for Assesing The Sustainability of Forest Management

Kelestarian pengelolaan hutan merupakan konsep yang samar dan kompleks, oleh karena itu tidak ada satupun alat ukur yang dapat mengukurnya secara jelas. Sertifikasi hutan digunakan sebagai instrumen untuk mengukur kelestarian pengelolaan hutan yang didasarkan atas kelestarianproduksi, ekologi dan sosial. Kriteria dan Indikator (C & I) untuk kelestarian hutan alam produksi dalam sistem sertifikasi di Indonesia (Lembaga Ekolabel Indonesia) menggunakan Analytical Hierarchy Process (AHP) sebagai alat dalam proses pengambilan keputusannya. AHP telah lama dikritisi, antara lain karena pendekatan kompensatori menggunakan modellinier additive utilitas untuk mengintegrasikan -nilai baku. Riset ini bertujuan untuk menganalisa beberapa metoda aggregasi nilai baku sebagai alternatif untuk menilai kelestarian pengelolaan hutan. Fuzzy AHP dan Rule Base (Fuzzy Reasoning Method) dipelajari sebagai metode untuk mengatasi kekurangmampuan AHP dalam menangani secara tepat peubah-peubah linguistik. Data hasil proses penilaian sertifikasi Unit Pengelolaan Hutan Labanan, Kalimantan Timur,Indonesia digunakan untuk menilai kelestarian pengelolaan hutan dengan tiga metode tersebut. Hasil Fuzzy AHP dibanding dengan Normal AHP menunjukkan hasil yeng lebih jelas dan sudah menampung ketidakpastian justifikasi ekspert yang tidak terdapat dalam Normal AHP. Metode Rule Base, yang sangat tergantung kepada pengetahuan dan pengalaman ekspertnya, memberikan hasil yang lebih berarti dan transparan dalam proses penilaian dibanding kedua metode lainnya, yaitu Normal AHP dan Fuzzy AHP.Keywords:  SFM assessment, forest certification, fuzzy decision making, AHP, Fuzzy AHP, Fuzzy Rule Bas

A fuzzy hierarchical decision model and its application in networking datacenters and in infrastructure acquisitions and design

According to several studies, an inordinate number of major business decisions to acquire, design, plan, and implement networking infrastructures fail. A networking infrastructure is a collaborative group of telecommunications systems providing services needed for a firm\u27s operations and business growth. The analytical hierarchy process (AHP) is a well established decision-making process used to analyze decisions related to networking infrastructures. AHP is concerned with decomposing complex decisions into a set of factors and solutions. However, AHP has difficulties in handling uncertainty in decision information. This study addressed the research question of solutions to AHP deficiencies. The solutions were accomplished through the development of a model capable of handling decisions with incomplete information and uncertain decision operating environment. This model is based on AHP framework and fuzzy sets theory. Fuzzy sets are sets whose memberships are gradual. A member of a fuzzy set may have a strong, weak, or a moderate membership. The methodology for this study was based primarily on the analytical research design method, which is neither quantitative nor qualitative, but based on mathematical concepts, proofs, and logic. The model\u27s constructs were verified by a simulated practical case study based on current literature and the input of networking experts. To further verify the research objectives, the investigator developed, tested, and validated a software platform. The results showed tangible improvements in analyzing complex networking infrastructure decisions. The ability of this model to analyze decisions with incomplete information and uncertain economic outlook can be employed in the socially important areas such as renewable energy, forest management, and environmental studies to achieve large savings

Towards effective consideration of non-financial factors in the design and management of construction assets.

The decisive role of non-financial factors in the design and management of construction assets is highlighted and existing techniques used to include these factors in the decision-making process are critically reviewed. An effective algorithm has been developed to include non-monetary benefits of competing design alternatives in whole-life costing studies. The unique feature of the algorithm, amongst others, is that it proceeds through logical steps that can be followed and assessed by decision-makers. Details of the computer implementation of the algorithm are presented. The solution of a selected example problem is also included to illustrate the theory of the algorithm

Multicriteria Personnel Selection by the Modified Fuzzy VIKOR Method

Personnel evaluation is an important process in human resource management. The multicriteria nature and the presence of both qualitative and quantitative factors make it considerably more complex. In this study, a fuzzy hybrid multicriteria decision-making (MCDM) model is proposed to personnel evaluation. This model solves personnel evaluation problem in a fuzzy environment where both criteria and weights could be fuzzy sets. The triangular fuzzy numbers are used to evaluate the suitability of personnel and the approximate reasoning of linguistic values. For evaluation, we have selected five information culture criteria. The weights of the criteria were calculated using worst-case method. After that, modified fuzzy VIKOR is proposed to rank the alternatives. The outcome of this research is ranking and selecting best alternative with the help of fuzzy VIKOR and modified fuzzy VIKOR techniques. A comparative analysis of results by fuzzy VIKOR and modified fuzzy VIKOR methods is presented. Experiments showed that the proposed modified fuzzy VIKOR method has some advantages over fuzzy VIKOR method. Firstly, from a computational complexity point of view, the presented model is effective. Secondly, compared to fuzzy VIKOR method, it has high acceptable advantage compared to fuzzy VIKOR method

A Spatial Fuzzy Compromise Approach for Flood Disaster Management

Natural disasters affect regions with different intensity and produce damages that vary in space. Topographical features of the region; location of properties that may be exposed to the peril; level of exposure; impact of different mitigation measures; are all variables with considerable spatial variability. A new method for evaluation of disaster impacts has been presented in this report that takes into consideration spatial variability of variables involved and associated uncertainty. Flood management has been used to illustrate the utility of proposed approach. Floodplain management is a spatial problem. Representation of flood damage mitigation alternatives and objectives in space provides a better insight into the management problem and its characteristics. Protection of a region from floods can be achieved through various structural and non-structural measures. Comparison of different measures and evaluation of their impacts is based on the multiple criteria. If they are described spatially, decision-making problem can be conceptualized as spatial multi criteria decision-making (MCDM). Tkach and Simonovic (1997) introduced spatial Compromise Programming (SPC) technique to account for spatial variability in flood management. Some of the criteria and preferences of the stakeholders involved with flood management are subject to uncertainty that may originate in the data, knowledge of the domain or our ability to adequately describe the decision problem. The main characteristic of flood management is the existence of objective and subjective uncertainty. Fuzzy set theory has been successfully used to address both, objective and subjective uncertainty. Bender and Simonovic (2000) incorporated vagueness and imprecision as sources of uncertainty into multi criteria decision-making in water resources. In this report a new technique named Spatial Fuzzy Compromise Programming (SFCP) has been developed to enhance our ability to address the issues related to uncertainties in spatial environment. A general fuzzy compromise programming technique, when made 2 spatially distributed, proved to be a powerful and flexible addition to the list of techniques available for decision making where multiple criteria are used to judge multiple alternatives. All uncertain variables (subjective and objective) are modeled by way of fuzzy sets. In the present study, fuzzy measures have been introduced to spatial multi criteria decision-making in the GIS environment in order to account for uncertainties. Through a case study of the Red River floodplain near the City of St. Adolphe in Manitoba, Canada, it has been illustrated that the new technique provides measurable improvement in flood management. Final results in the form of maps that shown spatial distribution of the impacts of mitigation measures on the region can be of great value to insurance industry.https://ir.lib.uwo.ca/wrrr/1004/thumbnail.jp

A review of fuzzy AHP methods for decision-making with subjective judgements

Analytic Hierarchy Process (AHP) is a broadly applied multi-criteria decision-making method to determine the weights of criteria and priorities of alternatives in a structured manner based on pairwise comparison. As subjective judgments during comparison might be imprecise, fuzzy sets have been combined with AHP. This is referred to as fuzzy AHP or FAHP. An increasing amount of papers are published which describe different ways to derive the weights/priorities from a fuzzy comparison matrix, but seldomly set out the relative benefits of each approach so that the choice of the approach seems arbitrary. A review of various fuzzy AHP techniques is required to guide both academic and industrial experts to choose suitable techniques for a specific practical context. This paper reviews the literature published since 2008 where fuzzy AHP is applied to decision-making problems in industry, particularly the various selection problems. The techniques are categorised by the four aspects of developing a fuzzy AHP model: (i) representation of the relative importance for pairwise comparison, (ii) aggregation of fuzzy sets for group decisions and weights/priorities, (iii) defuzzification of a fuzzy set to a crisp value for final comparison, and (iv) consistency measurement of the judgements. These techniques are discussed in terms of their underlying principles, origins, strengths and weakness. Summary tables and specification charts are provided to guide the selection of suitable techniques. Tips for building a fuzzy AHP model are also included and six open questions are posed for future work

Aggregation Methods for Assesing The Sustainability of Forest Management

Kelestarian pengelolaan hutan merupakan konsep yang samar dan kompleks, oleh karena itu tidak ada satupun alat ukur yang dapat mengukurnya secara jelas. Sertifikasi hutan digunakan sebagai instrumen untuk mengukur kelestarian pengelolaan hutan yang didasarkan atas kelestarianproduksi, ekologi dan sosial. Kriteria dan Indikator (C & I) untuk kelestarian hutan alam produksi dalam sistem sertifikasi di Indonesia (Lembaga Ekolabel Indonesia) menggunakan Analytical Hierarchy Process (AHP) sebagai alat dalam proses pengambilan keputusannya. AHP telah lama dikritisi, antara lain karena pendekatan kompensatori menggunakan modellinier additive utilitas untuk mengintegrasikan -nilai baku. Riset ini bertujuan untuk menganalisa beberapa metoda aggregasi nilai baku sebagai alternatif untuk menilai kelestarian pengelolaan hutan. Fuzzy AHP dan Rule Base (Fuzzy Reasoning Method) dipelajari sebagai metode untuk mengatasi kekurangmampuan AHP dalam menangani secara tepat peubah-peubah linguistik. Data hasil proses penilaian sertifikasi Unit Pengelolaan Hutan Labanan, Kalimantan Timur,Indonesia digunakan untuk menilai kelestarian pengelolaan hutan dengan tiga metode tersebut. Hasil Fuzzy AHP dibanding dengan Normal AHP menunjukkan hasil yeng lebih jelas dan sudah menampung ketidakpastian justifikasi ekspert yang tidak terdapat dalam Normal AHP. Metode Rule Base, yang sangat tergantung kepada pengetahuan dan pengalaman ekspertnya, memberikan hasil yang lebih berarti dan transparan dalam proses penilaian dibanding kedua metode lainnya, yaitu Normal AHP dan Fuzzy AHP.Keywords:  SFM assessment, forest certification, fuzzy decision making, AHP, Fuzzy AHP, Fuzzy Rule Bas