scholarly journals A New Approach to Assessing the Biases of Decisions based on Multiple Attribute Decision making Methods

2012 ◽  
Vol 117 (1) ◽  
Author(s):  
R. Simanaviciene ◽  
L. Ustinovicius
2018 ◽  
Vol 10 (12) ◽  
pp. 4451 ◽  
Author(s):  
Sarfaraz Hashemkhani Zolfani ◽  
Edmundas Kazimieras Zavadskas ◽  
Payam Khazaelpour ◽  
Fausto Cavallaro

Over the past few centuries, the process of decision-making has become more complicated in different respects. Since the initial phase of Multiple Criteria Decision Making (MCDM) around fifty years ago, Multiple Attribute Decision Making (MADM) has continued developing over the years as a sub-concept of MCDM. Noticeably, the importance of the decision-making process is increasingly expanding to such an extent that it necessarily blends into the undeniable processes of MADM actual models. Novel methods with different perspectives have been introduced considering the dynamic MADM concepts of time and future in classical frameworks; however, they do not overcome challenges in practice. Recently, Prospective MADM (PMADM) as a specific approach has presented future-oriented models using already known approaches of MCDM, and it has innovative items which show barriers of classic model of MADM. However, PMADM practically needs more conceptual bases to illustrate and plan the future of real decision-making problems. The Multi-Aspect Criterion is a new concept in mapping the future of the PMADM outline. In this regard, two examples of sustainability will be analyzed, and different requirements and aspects associated with PMADM will be discussed in this study. This new approach can support the PMADM outline in more detail and deal with a decision-making structure that can be considered as novel to industry experts.


2016 ◽  
Vol 22 (2) ◽  
pp. 309-326 ◽  
Author(s):  
Sarfaraz HASHEMKHANI ZOLFANI ◽  
Reza MAKNOON ◽  
Edmundas Kazimieras ZAVADSKAS

In recent years futures science has received a great deal of attention and has gained worldwide credibility in the science community as the science of tomorrows. The countless applications of futures studies in various fields have been a major breakthrough for mankind. Undoubtedly, decision making is one of the most significant aspects of shaping the future and an integral part of any credible future research. Multiple Criteria Decision Making (MCDM) in general and Multiple Attribute Decision Making in particular (MADM), are among the most remarkable subparts of the decision making process. The most recent model developed using the MADM method is the Dynamic MADM. The model does not specifically concentrate on the future actions and approaches and remains to be fully explored. This research presents a new concept and a new approach in the MADM field which is called the Prospective Multiple Attribute Decision Making (PMADM). The PMADM model can very well cover the DMADM concept but instead chooses to focus on future topics. The study also introduces two new approaches. The first research aims to elaborate the basis of this model and then evolves to deal with the future limiters as they potentially pop up and change the course of future actions. The new model based on future limiters is separated and categorized into two sections; one of which is looked upon without the probabilities rate and the other one with the probabilities rate. This approach is deemed priceless due to its major applicability in the ranking of the MADM methods such as: TOPSIS, VIKOR, COPRAS, ARAS, WASPAS and etc. Finally, a case study with the various applications of PMADM model in WASPAS methodology is put forth and illustrated.


2016 ◽  
Vol 20 (1) ◽  
pp. 101-111 ◽  
Author(s):  
Sarfaraz HASHEMKHANI ZOLFANI ◽  
Reza MAKNOON

Decision making takes into account a myriad of factors about the future topics, which often prove challenging and quite complicated. Multiple Attribute Decision-Making (MADM) methods still have not become powerful enough to help decision makers to adopt the best solutions regarding future issues. Different scenarios are suitable for developing an appropriate outlook toward different probable futures. Scenarios are not inherently quantitative, but recently different integrated quantitative methods have been incorporated with the processes in various studies. Previously, different types of scenario-based MADM methods have been presented in different studies, but they just considered each case separately. In those studies, MADM methods were only applied to evaluate the situation in scenario-based MADM. This research concentrates on another paradigm in applying scenarios to upcoming events, MADM methods in the new area are explored, and the concept, which is called MADM based scenarios, is presented. In different situations and scenarios, different MADM models will happen. New concepts about most useful criterion and applicable alternatives are introduced in this new approach for decision-making about the future. In addition, a general framework is proposed for applying MADM-based scenarios for unpredictable scenarios and situations, which can be almost controlled future in practice.


Mathematics ◽  
2019 ◽  
Vol 7 (7) ◽  
pp. 594 ◽  
Author(s):  
Mi Jung Son ◽  
Jin Han Park ◽  
Ka Hyun Ko

As an extension of the fuzzy set, the hesitant fuzzy set is used to effectively solve the hesitation of decision-makers in group decision-making and to rigorously express the decision information. In this paper, we first introduce some new hesitant fuzzy Hamacher power-aggregation operators for hesitant fuzzy information based on Hamacher t-norm and t-conorm. Some desirable properties of these operators is shown, and the interrelationships between them are given. Furthermore, the relationships between the proposed aggregation operators and the existing hesitant fuzzy power-aggregation operators are discussed. Based on the proposed aggregation operators, we develop a new approach for multiple-attribute decision-making problems. Finally, a practical example is provided to illustrate the effectiveness of the developed approach, and the advantages of our approach are analyzed by comparison with other existing approaches.


2018 ◽  
Vol 1 (2) ◽  
pp. 45-54
Author(s):  
Helpi Nopriandi

Tenaga Kependidikan merupakan anggota masyarakat yang mengabdikan diri dan diangkat untuk menunjang penyelenggaraan pendidikan. Decision Support Systems atau lebih dikenal dengan Sistem Pendukung Keputusan adalah bagian dari sebuah sistem informasi yang berbasis komputer termasuk sistem yang berbasis ilmu pengetahuan dan dipakai untuk mendukung pengambil  keputusan dalam suatu organisasi atau perusahaan. untuk memudahkan pimpinan dalam mengambil sebuah keputusan dibuatlah suatu sistem pengambil keputusan dengan menggunakan Fuzzy Multiple Attribute Decision Making  (FMADM) digunakan untuk mencari alternatif optimalkan dari sejumlah alternatif dengan kriteria tertentu, sedangkan metode Simple Additive Weighting (SAW). Metode SAW sering juga dikenal istilah metode penjumlahan terbobot. Konsep dasar metode SAW adalah mencari penjumlahan terbobot dari rating kinerja pada setiap alternatif dari semua atribut.


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