scholarly journals Two Hesitant Multiplicative Decision-Making Algorithms and Their Application to Fog-Haze Factor Assessment Problem

Algorithms ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 154 ◽  
Author(s):  
Lidan Pei ◽  
Feifei Jin
Keyword(s):  
Decision Making ◽  
Preference Relation ◽  
Linear Optimization ◽  
Iterative Algorithms ◽  
Weight Vector ◽  
Factors Affecting ◽  
Linear Optimization Model ◽  
New Concepts ◽  
Priority Weights ◽  
Hesitant Multiplicative Preference Relation

Hesitant multiplicative preference relation (HMPR) is a useful tool to cope with the problems in which the experts utilize Saaty’s 1–9 scale to express their preference information over paired comparisons of alternatives. It is known that the lack of acceptable consistency easily leads to inconsistent conclusions, therefore consistency improvement processes and deriving the reliable priority weight vector for alternatives are two significant and challenging issues for hesitant multiplicative information decision-making problems. In this paper, some new concepts are first introduced, including HMPR, consistent HMPR and the consistency index of HMPR. Then, based on the logarithmic least squares model and linear optimization model, two novel automatic iterative algorithms are proposed to enhance the consistency of HMPR and generate the priority weights of HMPR, which are proved to be convergent. In the end, the proposed algorithms are applied to the factors affecting selection of fog-haze weather. The comparative analysis shows that the decision-making process in our algorithms would be more straight-forward and efficient.

A novel group decision making method for interval-valued pythagorean fuzzy preference relations

2021 ◽  
pp. 1-23
Author(s):  
Ziyu Yang ◽  
Liyuan Zhang ◽  
Tao Li
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Programming Model ◽  
Preference Relation ◽  
Uncertain Information ◽  
Multiplicative Consistency ◽  
Priority Weights ◽  
Interval Valued ◽  
Fuzzy Preference

Interval-valued Pythagorean fuzzy preference relation (IVPFPR) plays an important role in representing the complex and uncertain information. The application of IVPFPRs gives better solutions in group decision making (GDM). In this paper, we investigate a new method to solve GDM problems with IVPFPRs. Firstly, novel multiplicative consistency and consensus measures are proposed. Subsequently, the procedure for improving consistency and consensus levels are put forward to ensure that every individual IVPFPR is of acceptable multiplicative consistency and consensus simultaneously. In the context of minimizing the deviations between the individual and collective IVPFPRs, the objective experts’ weights are decided according to the optimization model and the aggregated IVPFPR is derived. Afterwards, a programming model is built to derive the normalized Pythagorean fuzzy priority weights, then the priority weights of alternatives are identified as well. An algorithm for GDM method with IVPFPRs is completed. Finally, an example is cited and comparative analyses with previous approaches are conducted to illustrate the applicability and effectiveness of the proposed method.

scholarly journals Additively Consistent Interval-Valued Intuitionistic Fuzzy Preference Relations and Their Application to Group Decision Making

Information ◽  
2018 ◽  
Vol 9 (10) ◽  
pp. 260 ◽  
Author(s):  
Hua Zhuang
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Preference Relation ◽  
Weighted Averaging ◽  
Preference Relations ◽  
Intuitionistic Fuzzy ◽  
Priority Weights ◽  
Interval Valued ◽  
Fuzzy Preference

This paper aims to propose an innovative approach to group decision making (GDM) with interval-valued intuitionistic fuzzy (IVIF) preference relations (IVIFPRs). First, an IVIFPR is proposed based on the additive consistency of an interval-valued fuzzy preference relation (IVFPR). Then, two mathematical or adjusted programming models are established to extract two special consistent IVFPRs. In order to derive the priority weight of an IVIFPR, after taking the two special IVFPRs into consideration, a linear optimization model is constructed by minimizing the deviations between individual judgments and between the width degrees of the interval priority weights. For GDM with IVIFPRs, the decision makers’ weights are generated by combining the adjusted subjective weights with the objective weights. Subsequently, using an IVIF-weighted averaging operator, the collective IVIFPR is obtained and utilized to derive the IVIF priority weights. Finally, a practical example of a supplier selection is analyzed to demonstrate the application of the proposed method.

scholarly journals Consensus-Based Multi-Person Decision Making with Incomplete Fuzzy Preference Relations Using Product Transitivity

Mathematics ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 185 ◽  
Author(s):  
Atiq-ur Rehman ◽  
Mustanser Hussain ◽  
Adeel Farooq ◽  
Muhammad Akram
Keyword(s):  
Decision Making ◽  
Preference Relation ◽  
Selection Procedure ◽  
Feedback Mechanism ◽  
Decision Makers ◽  
Consensus Process ◽  
Preference Relations ◽  
Priority Weights ◽  
Fuzzy Preference Relations ◽  
Fuzzy Preference

In this paper, a consensus-based method for multi-person decision making (MPDM) using product transitivity with incomplete fuzzy preference relations (IFPRs) is proposed. Additionally, an average aggregation operator has been used at the first level to estimate the missing preference values and construct the complete fuzzy preference relation (FPR). Then it is confirmed to be product consistent by using the transitive closure formula. Following this, weights of decision makers (DMs) are evaluated by merging consistency weights and predefined priority weights (if any). The consistency weights for the DMs are estimated through product consistency investigation of the information provided by each DM. The consensus process determines whether the selection procedure should be initiated or not. The hybrid comprises of a quitting process and feedback mechanism, and is used to enhance the consensus level amongst DMs in case of an inadequate state. The quitting process arises when some DMs decided to leave the course, and is common in MPDM while dealing with a large number of alternatives. The feedback mechanism is the main novelty of the proposed technique which helps the DMs to improve their given preferences based on this consistency. At the end, a numerical example is deliberated to measure the efficiency and applicability of the proposed method after the comparison with some existing models under the same assumptions. The results show that proposed method can offer useful comprehension into the MPDM process.

Decision-Making Models Based on Satisfaction Degree with Incomplete Hesitant Fuzzy Preference Relation

2021 ◽  
Author(s):  
Jian Li ◽  
Li-li Niu ◽  
Qiongxia Chen ◽  
Zhong-xing Wang
Keyword(s):  
Decision Making ◽  
Programming Model ◽  
Preference Relation ◽  
Weight Vector ◽  
Decision Makers ◽  
Fuzzy Preference Relation ◽  
Satisfaction Degree ◽  
Hesitant Fuzzy Preference Relation ◽  
Decision Making Models ◽  
Fuzzy Preference

Abstract To address the situation where the incomplete hesitant fuzzy preference relation (IHFPR) is necessary, this paper develops decision-making models based on decision makers’ satisfaction degree with IHFPR. First, the consistency measures from the perspectives of additive and multiplicative consistent IHFPR are defined based on the relationships between the IHPFRs and their corresponding priority weight vector, respectively. Second, two decision-making models are developed in view of the proposed additive and multiplicative consistency measures. The main characteristic of the constructed model sarethey taking into account the decision makers’ satisfaction degree. The objective functions of the models are developed by maximizing the parameter of satisfaction degree. Third, a square programming model is developed to obtain the decision makers’ weights byutilizing the optimal priority weight vectors information, the solution of the model is obtained by solving the partial derivatives ofLagrange function.Finally, a procedure for multi-criteria decision-making (MCDM) problems with IHFPRs is given, and an illustrative example in conjunction with comparative analysis is used to demonstrate the proposed models are feasible and efficiency for practical MCDM problems.

An exploration of FMCDM approach for evaluating the outcome/success of GSD projects

2013 ◽  
Vol 3 (3) ◽  
Author(s):  
Arun Sangaiah ◽  
Arun Thangavelu
Keyword(s):  
Decision Making ◽  
Influential Factors ◽  
Three Dimensions ◽  
Quality Factors ◽  
Factors Affecting ◽  
Partnership Quality ◽  
Project Outcome ◽  
Priority Weights ◽  
Quality Dimensions ◽  
The Impact

AbstractThis study presents a fuzzy multi-criteria decision making (FMCDM) approach for analyzing the influential factors affecting the outcome/success of global software development (GSD) projects. The main aim of this study is to demonstrate the potential of proposed methodology based on FMCDM which is used to measure the offshore/onsite teams’ partnership quality dimensions and underlying the influential factors towards the outcome of GSD projects. The uncertainty and subjective vagueness within the decision making process are dealing with fuzzy linguistic terms quantified in an interval scale [0,1]. The proposed FMDCM framework is used to determine the priority weights of partnership quality factors and rating the GSD project outcome/success from the service provider perspective into three dimensions: service quality, schedule and cost improvement. The predicted GSD project outcome values are obtained to facilitate organization and to determine the impact of offshore/on-site teams’ partnership quality towards success of GSD project outcome otherwise initiate actions to improve the GSD project outcome. This study established survey research method that involves thirty-eight critical influential factors evaluated by twenty software professionals for their assessment of GSD projects outcome in India.

scholarly journals Pavement Maintenance Decision Making Based on Optimization Models

2021 ◽  
Vol 11 (20) ◽  
pp. 9706
Author(s):  
Shitai Bao ◽  
Keying Han ◽  
Lan Zhang ◽  
Xudong Luo ◽  
Shunqing Chen
Keyword(s):  
Decision Making ◽  
Optimization Model ◽  
Linear Optimization ◽  
Condition Index ◽  
Maintenance Costs ◽  
Pavement Condition ◽  
Pavement Maintenance ◽  
Linear Optimization Model ◽  
Decision Making Problem ◽  
Pavement Condition Index

Pavement maintenance prioritization considering both quality and cost is an important decision-making problem. In this paper, the actual pavement condition index of city roads was calculated using municipal patrol data. A linear optimization model that maximized maintenance quality with limited maintenance costs and a multi-objective optimization model that maximized maintenance quality while minimizing maintenance costs were developed based on the pavement condition index. These models were subsequently employed in making decisions for actual pavement maintenance using sequential quadratic programming and a genetic algorithm. The results showed that the proposed decision-making models could effectively address actual pavement maintenance issues. Additionally, the results of the single-objective linear optimization model verified that the multiobjective optimization model was accurate. Thus, they could provide optimal pavement maintenance schemes for roads according to actual pavement conditions. The reliability of the models was investigated by analyzing their assumptions and validating their optimization results. Furthermore, their applicability in pavement operation-related decision making and preventive maintenance for roads of different grades was confirmed.

Segments Influencing Individual Investors Behavior And Their Investment Decision

2019 ◽  
Vol 118 (9) ◽  
pp. 154-160
Author(s):  
Dr. Kartikey Koti
Keyword(s):  
Decision Making ◽  
Social Factors ◽  
Stock Markets ◽  
Investment Decision ◽  
Individual Investors ◽  
Factors Affecting ◽  
The Social ◽  
Karnataka State ◽  
Essential Idea

The essential idea of this assessment is investigate the social factors affecting particular theorists' decisions making limit at Indian Stock Markets. In the examination coordinated standard of direct is Classified subject to two estimations the first is Heuristic (Decision making) and the resulting one is prospect.. For the assessment coordinated the data used is basic natured which is assembled through a sorted out survey from 100 individual money related authorities based out in Hubli and Dharwad city, Karnataka State in India on an accommodating way. The respondents were both sex and overwhelming part male were 68% . These theorists were having a spot with the age bundle between35-45 which is 38%. These respondents have completed their graduation were around 56%. These respondents had work inclusion of 5 to 10 years which is 45% and the majority of which were used in government portion which is 56%. Their compensation was between 4 to 6 Lakh and were fit for placing assets into business areas. The money related experts were widely masterminded placing assets into different portfolios like 32% in Share market and 20 % in Fixed store. These examiners mode to known various endeavor streets were through News, family and allies.  

The Paradox of Poverty: Socio-Economic Aspects of Population Growth.— By T. Scarlett Epstein and Darrell Jackson. The Macmillan of India Limited Delhi, 1975. pp.127.

1978 ◽  
Vol 17 (3) ◽  
pp. 380-382
Author(s):  
M. Javed Akbar Zaki
Keyword(s):  
Decision Making ◽  
Social Situation ◽  
Economic Security ◽  
Rural India ◽  
Factors Affecting ◽  
Number Of Children ◽  
Economic Progress ◽  
The Poor ◽  
Fertility Decision ◽  
The Social

To many social theoreticians, the population explosion, particularly in the developing nations presents a crippling threat to their developmental pro¬cesses. Their argument's validity rests mainly on the assumption that expected economic progress is swallowed up by unbalanced rise of numbers in the population. The book being reviewed deals mainly with this subject matter and is divided into two parts, each containing three articles contributed by various researchers. Part one, 'The Social context of Fertility Decision' is focused on analyzing the role of factors affecting fertility at the micro-level decision making process. The first article 'Fertility decision in rural India' by Vinod Jainath, examines the applicability to rural India of various models of the process of fertility decision making and finds most of these wanting with respect to the Indian social situation. While analyzing the fertility patterns of Rural India, he points out the positive need for larger families among the poor small farmers mainly due to labour supply considerations. The author argues that unemployment and under¬employment actually motivate the poor to have more children as it better ensures their economic security in their old age. As the chances of gaining employ¬ment for their offspring diminish, they are induced to increase the total number of children in order that atleast one will be able to support them. Thus a vicious circle of poverty arises in large families because of each of the parents wanting to increase their children's chances of employment by ultimately reducing the overall employment opportunities even further and exacerbating their poverty.

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