Preference Coalition Formation Scheme for Buyer Coalition Services with Bundles of Items

Author(s):  
Laor Boongasame ◽  
Dickson K. W. Chiu

Coalition stability is a major requirement in coalition formation. One important problem to achieve stability in n-person game theories is the assumption that the preference of each buyer is publicly known. The coalition is said to be stable if there are no objection by any subset of buyers according to their publicly known preferences. However, such assumption is often unrealistic in typical real-life situations. Individual buyers often have private preferences and make their decisions according to their own preferences instead. This study proposes a novel preference coalition formation scheme for buyer coalition services that attempts to consider private preference of individual buyers within the buyer coalition process. The theoretical foundations of the study are rooted in the fields of multi-criteria decision making, human practical reasoning, and n-person game theories, from which we design an appropriate scheme for our proposed buyer coalition framework with emphasis on private preferences of individual buyers. The authors validate their proposed scheme with simulation software developed to demonstrate results of a variety of practical situations.

Symmetry ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 1351
Author(s):  
Rashad Aliyev ◽  
Hasan Temizkan ◽  
Rafig Aliyev

High competition between universities has been increasing over the years, and stimulates higher education institutions to attain higher positions in the ranking list. Ranking is an important performance indicator of university status evaluation, and therefore plays an essential role in students’ university selection. The ranking of universities has been carried out using different techniques. Main goal of decision processes in real-life problems is to deal with the symmetry or asymmetry of different types of information. We consider that multi-criteria decision making (MCDM) is well applicable to symmetric information modelling. Analytic hierarchy process (AHP) is a well-known technique of MCDM discipline, and is based on pairwise comparisons of criteria/alternatives for alternatives’ evaluation. Unfortunately, the classical AHP method is unable to deal with imprecise, vague, and subjective information used for the decision making process in complex problems. So, introducing a more advanced tool for decision making under such circumstances is inevitable. In this paper, fuzzy analytic hierarchy process (FAHP) is applied for the comparison and ranking of performances of five UK universities, according to four criteria. The criteria used for the evaluation of universities’ performances are teaching, research, citations, and international outlook. It is proven that applying FAHP approach makes the system consistent, and by the calculation of coefficient of variation for all alternatives, it becomes possible to rank them in prioritized order.


2020 ◽  
Vol 7 (12) ◽  
pp. 133-143
Author(s):  
Şeyma Emeç ◽  
Gökay Akkaya

The problem of a warehouse location selecting which has a significant impact on logistics costs is an important decision problem based on the best choice of alternatives under multiple conflicting criteria. Multiple-criteria decision-making (MCDM) methods are used as a solution approach for the decision problems including several criteria. In this study, a new stochastic multi-criteria decision-making approach has been developed to solve the warehouse location selection problem (WLSP) in the stochastic environment which contains uncertain situations. In the proposed approach, the SAHP (Stochastic Analytic Hierarchy Process) method was used to calculate the weight of criteria, and the alternatives were ranked and evaluated by fuzzy MOORA (Multi-Objective Optimization by Ratio Analysis). The proposed approach is applied to warehouse selection problem of a supermarket chain located in Turkey. The results of the research indicated that A2 is the best alternative. It can be said that the proposed method can be applied to the real life problems because it found a suitable solution to the problem.


Symmetry ◽  
2020 ◽  
Vol 12 (4) ◽  
pp. 618 ◽  
Author(s):  
Nguyen Tho Thong ◽  
Florentin Smarandache ◽  
Nguyen Dinh Hoa ◽  
Le Hoang Son ◽  
Luong Thi Hong Lan ◽  
...  

Dynamic multi-criteria decision-making (DMCDM) models have many meaningful applications in real life in which solving indeterminacy of information in DMCDMs strengthens the potential application of DMCDM. This study introduces an extension of dynamic internal-valued neutrosophic sets namely generalized dynamic internal-valued neutrosophic sets. Based on this extension, we develop some operators and a TOPSIS method to deal with the change of both criteria, alternatives, and decision-makers by time. In addition, this study also applies the proposal model to a real application that facilitates ranking students according to attitude-skill-knowledge evaluation model. This application not only illustrates the correctness of the proposed model but also introduces its high potential appliance in the education domain.


2021 ◽  
Vol 40 (1) ◽  
pp. 565-573
Author(s):  
Di Zhang ◽  
Pi-Yu Li ◽  
Shuang An

In this paper, we propose a new hybrid model called N-soft rough sets, which can be seen as a combination of rough sets and N-soft sets. Moreover, approximation operators and some useful properties with respect to N-soft rough approximation space are introduced. Furthermore, we propose decision making procedures for N-soft rough sets, the approximation sets are utilized to handle problems involving multi-criteria decision-making(MCDM), aiming at electing the optional objects and the possible optional objects based on their attribute set. The algorithm addresses some limitations of the extended rough sets models in dealing with inconsistent decision problems. Finally, an application of N-soft rough sets in multi-criteria decision making is illustrated with a real life example.


2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Gulsah Hancerliogullari Koksalmis

Elective course selection has always been a serious and important decision making process for students in institutions.  The study of Multi Criteria Decision Making Model (MCDM) for the selection of elective course is put together with the aim of lending a helping hand to the students. It comprises the main MCDM methods, the problem of selecting an elective course, the survey about the problem, the method which is selected to be implemented, the implementation and the results. In this study, we determine the criteria of this problem for graduate students while deciding on the elective courses. A total of 13 different criteria have been established, including 5 main criteria. In this direction, a questionnaire study was conducted as required by the multi-criteria decision-making analysis method decided in the light of the examined articles. This survey study was answered by graduate students. The responses were evaluated by the "Super Decisions" program and priorities were determined using the Analytic Hierarchy Process (AHP). The survey was applied to graduate students, and it was found that the two most important criteria of the graduate students were 28.03% of the curriculum and 20.42% of the faculty members. This study aims to prove a mathematical method for a real-life situation which can help people make their decisions accurately. It will help students who are indecisive and hesitates while selecting an elective course.


2021 ◽  
Vol 21 (1) ◽  
pp. 3-18
Author(s):  
Melda Kokoç ◽  
Süleyman Ersöz

Abstract Many authors agree that the Interval-Valued Intuitionistic Fuzzy Set (IVIFS) theory generates as realistic as possible evaluation of real-life problems. One of the real-life problems where IVIFSs are often preferred is the Multi-Criteria Decision-Making (MCDM) problem. For this problem, the ranking of values obtained by fuzzing the opinions corresponding to alternatives is an important step, as a failure in ranking may lead to the selection of the wrong alternative. Therefore, the method used for ranking must have high performance. In this article, a new score function SKE and a new accuracy function HKE are developed to overcome the disadvantages of existing ranking functions for IVIFSs. Then, two illustrative examples of MCDM problems are presented to show the application of the proposed functions and to evaluate their effectiveness. Results show that the functions proposed have high performance and they are the eligibility for the MCDM problem.


Author(s):  
Tolga Temucin

Multi-criteria decision making (MCDM) is a discipline that explicitly considers assessing alternatives in a decision problem with respect to multiple criteria. Those methods are frequently used to solve real-life decision problems that incorporate multiple, conflicting, and incommensurate criteria. Considering the chaotic, complex, and ambiguous nature and the dynamics of the military operations, most decision problems observed in military organizations also follow a similar structure involving multiple criteria. This chapter gives an overview of the basic decision-making problem types and decision processes observed in military organizations and provides information on the MCDM methodologies adopted to solve those problems.


Author(s):  
Bhagawati P. Joshi ◽  
Sanjay Kumar

In this study, the familiarity or expertise of the experts with the evaluation areas (called confidence levels) is also incorporated in the multi-criteria decision making (MCDM) process under intuitionistic fuzzy environment, i.e. two types of information is involved: one is the performance of the evaluation objects under intuitionistic fuzzy environment and other is the familiarity or expertise with the evaluation areas. In this direction recently, Yu (2014) proposed some operators to aggregate the two types information described above effectively. In this paper, the weighted confidence level is used instead of simply confidence levels as used by Yu (2014) to enhance MCDM method under intuitionistic fuzzy environment. So, two operators such as intuitionistic fuzzy weighted averaging operator under weighted confidence level (IFWAOUWCL) and intuitionistic fuzzy weighted geometric operator under weighted confidence level (IFWGOUWCL) are introduced to aggregate the two types of information. Finally, the presented technique is implemented effectively to a real life problem of supply selection.


Author(s):  
Tolga Temucin

Multi-criteria decision making (MCDM) is a discipline that explicitly considers assessing alternatives in a decision problem with respect to multiple criteria. Those methods are frequently used to solve real-life decision problems that incorporate multiple, conflicting, and incommensurate criteria. Considering the chaotic, complex, and ambiguous nature and the dynamics of the military operations, most decision problems observed in military organizations also follow a similar structure involving multiple criteria. This chapter gives an overview of the basic decision-making problem types and decision processes observed in military organizations and provides information on the MCDM methodologies adopted to solve those problems.


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