Genetic algorithm based fuzzy weighted average for multi-criteria decision making problems

We present the induced intuitionistic fuzzy ordered weighted averaging-weighted average (I-IFOWAWA) operator. It is a new aggregation operator that uses the intuitionistic fuzzy weighted average (IFWA) and the induced intuitionistic fuzzy ordered weighted averaging (I-IFOWA) operator in the same formulation. We study some of its main properties and we have seen that it has a lot of particular cases such as the IFWA and the intuitionistic fuzzy ordered weighted averaging (IFOWA) operator. We also study its applicability in a decision-making problem concerning strategic selection of investments. We see that depending on the particular type of I-IFOWAWA operator used, the results may lead to different decisions.

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Modeling Knowledge Employee’s Turnover Based on P-SVM

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.121-122.825 ◽

2010 ◽

Vol 121-122 ◽

pp. 825-831

Author(s):

Yong Zhao ◽

Ye Zheng Liu

Keyword(s):

Genetic Algorithm ◽

Decision Making ◽

Model Development ◽

Forecast Model ◽

Support Vector ◽

Multi Criteria Decision Making ◽

Parameters Selection ◽

Vector Machines ◽

Decision Making Problem ◽

Simulation Results

Knowledge employee’s turnover forecast is a multi-criteria decision-making problem involving various factors. In order to forecast accurately turnover of knowledge employees, the potential support vector machines(P-SVM) is introduced to develop a turnover forecast model. In the model development, a chaos algorithm and a genetic algorithm (GA) are employed to optimize P-SVM parameters selection. The simulation results show that the model based on potential support vector machine with chaos not only has much stronger generalization ability but also has the ability of feature selection.

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Multi-Criteria Decision-Making Techniques for Solving the Airport Ground Handling Service Equipment Vendor Selection Problem

Sustainability ◽

10.3390/su11123466 ◽

2019 ◽

Vol 11 (12) ◽

pp. 3466 ◽

Cited By ~ 1

Author(s):

Shen ◽

Peng ◽

Tu

Keyword(s):

Decision Making ◽

Goal Programming ◽

Quantitative Methods ◽

Weighted Average ◽

Fuzzy Topsis ◽

Programming Approach ◽

Vendor Selection ◽

Multi Criteria Decision Making ◽

Study Results ◽

Ground Handling

Appropriate airport ground handling service (AGHS) equipment vendor selection (AGHSEVS) can prevent aircraft damage and delays in airlines schedules, and ensure reliable and high-quality ground handling service. Previous research has seldom integrated multi-criteria decision-making techniques with goal programming to solve the AGHSEVS problem. This paper describes a new system evaluation model for AGHSEVS by considering both qualitative and quantitative methods. We compare the fuzzy TOPSIS method based on fuzzy weighted average left and right score methods with multi-choice and multi-aspiration goal programming approach of an AGHS company in Taiwan. These study results can help airport ground handling service company managers make optimal decisions for AGHSEVS problems. We hope the practicability of the comparable model with slight modifications of real situation data can be used in other AGHS companies.

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APPLICATION OF FUZZY ELECTRE METHOD WITH TRAPEZOIDAL FUZZY NUMBERS

World Science ◽

10.31435/rsglobal_ws/30082021/7654 ◽

2021 ◽

Author(s):

Salimov Vagif Hasan Oglu

Keyword(s):

Decision Making ◽

Test Problem ◽

Fuzzy Numbers ◽

Weighted Average ◽

Practical Implementation ◽

Pairwise Comparisons ◽

Multi Criteria Decision Making ◽

Linguistic Information ◽

Application Problem ◽

Electre Method

The article is devoted to the problem of multi-criteria decision-making. Methods for solving this problem can be divided into two large groups:methods using the aggregation of all alternatives according to all criteria and the solution of the resulting single-criterion problem. The second group isassociated with the procedure of pairwise comparisons and stepwise aggregation. The first group includes methods: weighted average sum,product and their various modifications, the second group includes - AHP, ELECTRE, TOPSIS, PROMETHEE, ELECTRE. For many problemsassessment of the criteria implemented by experts and presented in linguistic form. The effective approach for dealing with linguistic information is fuzzyset theory proposed by L. Zadeh. In this paper is proposed fuzzy ELECTRE method. This method is presented in details. As application problem is usedthe equipment selection problem The issues of practical implementation of this method are discussed in details. The results of the solution test problem at all stages are presented.

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Multi-Criteria Decision-Making Method Based on a Weighted 2-Tuple Fuzzy Linguistic Representation Model

International Journal of Information Technology & Decision Making ◽

10.1142/s0219622021500085 ◽

2021 ◽

pp. 1-16

Author(s):

Jia-Wen Wang

Keyword(s):

Decision Making ◽

Feature Selection Method ◽

Weighted Average ◽

Numerical Calculations ◽

Multi Criteria Decision Making ◽

Linguistic Representation ◽

Representation Model ◽

Priority Ranking ◽

Human Thinking ◽

Fuzzy Linguistic

Multi-criteria decision-making (MCDM) methods are used in the selection and evaluation of alternatives. However, too many decision criteria and numerical calculations will increase the computational complexity and make the calculation process difficult to understand. In this paper, a weighted 2-tuple fuzzy linguistic representation model is proposed. The contributions of this study are as follows: (1) Feature selection method was used to remove the redundant or irrelevant feature attributes, thereby simplifying calculations and reducing calculation complexities. (2) The integration of the 2-tuple linguistic representation model simplifies the complexity of numerical calculations. The calculation of qualitative scales can be closer to the human thinking model, and loss of information can be avoided during calculations through the appropriate model. (3) Information fusion technology, i.e., ordered weighted average operator (OWA), was used. The method simplifies the traditional OWA calculation and can be calculated according to the priority order of the indicators. (4) Four major shareholding companies in Taiwan 50 ETF stocks were selected as experimental cases. In total, 992 tuples were obtained and 29 technical indicators were analyzed. The results indicate that case A1 is the most stable among the four stocks considered under different decision-making situations, and it has the first priority ranking.

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