Complex intuitionistic fuzzy soft SWARA - COPRAS approach: An application of ERP software selection

<abstract><p>In this manuscript, we propose an integrated framework based on COmplex PRoportional ASsessment and Step-wise Weight Assessment Ratio Analysis approach within the complex intuitionistic fuzzy soft (CIFS) context. This context is an ideal technique with complex fuzzy foundation that means to denote multi-dimensional data in a concise. In this framework, criteria weights are evaluated by the SWARA technique, and the ranking of alternatives is determined by the COPRAS method using CIFSs. Further, to illustrate the applicability of the presented technique, an empirical case study of ERP software selection problem is taken. A comparative study and sensitivity analysis is presented to verify the strength of the presented methodology.</p></abstract>

An approach to optimize container locations in a containership with Electre III

In this article, we treat the problem of container storage in the export direction, exactly in the containership loading process. We propose an approach to the problem of container placement in a containership by describing a decision model to help decision-makers (handling operators) to minimize the total containers shifting. This is obtained by using a multicriteria decision method named Electre III (Elimination and Choice Expressing Reality) to identify the best location of any container. Here, we consider four criteria: the container destination, the container weight, the departure date of the container and the container type. This method has as input a matrix of performance and the subjective parameters and gives a ranking of alternatives as an output.

Comparison of Normalization Techniques on Data Sets with Outliers

With the fast growing of data-rich systems, dealing with complex decision problems with skewed input data sets and respective outliers is unavoidable. Generally, data skewness refers to a non-uniform distribution in a dataset, i.e. a dataset which contains asymmetries and/or outliers. Normalization is the first step of most multi-criteria decision making (MCDM) problems to obtain dimensionless data, from heterogeneous input data sets, that enable aggregation of criteria and thereby ranking of alternatives. Therefore, when in presence of outliers in criteria datasets, finding a suitable normalization technique is of utmost importance. As such, in this work, we compare seven normalization techniques (Max, Max-Min, Vector, Sum, Logarithmic, Target-based, and Fuzzification) on criteria datasets, which contain outliers to analyse their results for MCDM problems. A numerical example illustrates the behaviour of the chosen normalization techniques and an (ongoing) evaluation assessment framework is used to recommend the best normalization technique for this type of criteria.

A Review on Evaluation of MIG Welding Process Parameter by using MOORAS Method

This review paper focus on Parametric optimization in Metal inert gas welding by using MOORAS method. MIG is arc welding process. Parameters optimization can be done by Multi-objective optimization on basis of ratio analysis and analytical Heriachy process. Ranking of alternatives determine by attributes weight or related importance given between attributes and on the values of the selected attributes,MOORA method is very fast and robust. It needs minimum Mathematical calculations and calculations time. Review paper endeavor process to illustrate problem by MOORAS method.

Decision Support System for Employee Performance Using AHP Method

The system supports the company's performance appraisal using the AHP (Case Study: PT. Andhy Putra) method, one of which is to find, select, assess and determine the best employees every year to match the abilities and assessment criteria applied so far. PT. Andhy Putra while assessing employee performance, especially in CME and OSP, still experiences shortcomings and weaknesses in determining qualified employees. This employee performance system has problems in assessing the performance appraisal data that is less accurate, which is carried out on a paper-based basis and requires less efficient time and large costs. For that, we need a decision support system in helping PT. Andhy Putra to conduct a performance appraisal every year. The method used in this employee assessment is AHP (Analytical Hierarchy Process), which is often also known as the weighting method. The process hierarchy analytical method is one of the methods used to find weight values ​​based on existing criteria and helps facilitate the ranking of alternatives based on the distance between the positive ideal solution and the negative ideal solution. There are 5 (five) criteria as a tool to assess employee performance, namely commitment to the company, desire for achievement, cooperation, leadership and discipline accompanied by the results of the implementation of this process hierarchy method in the form of ranking the alternatives used. This decision support system is built using the PHP programming language and MySQL database

Observation of a Change in Human Attitude in a Decision Making Process Equipped with an Interference of a Third Party

In this paper, the attitudes of experts are observed for the possible changes after taking a certain decision. The decision is taken by two persons with different fields of expertise. There is also an annotation of such changes due to the interference of a third person, which is main idea of this paper. These observations are done by developing fuzzy soft differential equations with the help of optimum fuzzy soft constants (OFSCs), which are obtained through the ranking coefficients. The ranking of alternatives is based on the coefficients, which are obtained through a decision-making process. Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is exploited to rank the alternatives, and the attitudes of resource persons are examined through phase portraits and line graphs of the respective system of differential equations. The utilization of TOPSIS is a practice of multi-criteria decision-making in the analysis of human behaviours. Dual hesitant fuzzy soft sets are taken to represent the initial data.

PENSION SERVICE INSTITUTION SELECTION BY A PERSONALIZED QUANTIFIER-BASED MACONT METHOD

With the emergence of a variety of pension service institutions, how to choose a suitable institution has become a strategic decision-making problem faced by pension service demanders. To solve this problem, this study identifies key evaluation criteria of pension service institutions through the analysis of the relevant literature. Then, this study proposes a mixed aggregation by comprehensive normalization technique (MACONT) with a personalized quantifier to select pension service institutions, where the personalized qualifier with cubic spline interpolation is used to derive the position weights of criteria, and the MACONT is improved to determine the ranking of alternatives. A case study about the selection of pension service institutions is provided to verify the feasibility of the proposed model. It is found that the proposed method is effective in dealing with heterogeneous evaluation information, and the personalized quantifiers can be combined with MACONT methods to obtain an optimal solution associated with the attitude of pension service demanders. The identified key evaluation criteria are not only significant for pension service demanders, but also conducive to the further improvement of property management related to pension services.

Methodical Aspects of MCDM Based E-Commerce Recommender System

The aim of this paper is to present the use of an innovative approach based on MCDM methods as the main component of a consumer Decision Support System (DSS) by recommending the most suitable products among a given set of alternatives. This system provides a reliable recommendation to the consumer in the form of a compromise ranking constructed from the five MCDM methods: the hybrid approach TOPSIS-COMET, COCOSO, EDAS, MAIRCA, and MABAC. Each of the methods used contributes significantly to the final compromise ranking built with the Copeland strategy. Chosen MCDM methods were combined with the objective CRITIC weighting method, and their performance was presented on the illustrative example of choosing the most suitable mobile phone. A sensitivity analysis involving the rw and WS correlation coefficients was performed to determine the match between the compromise ranking of the candidates and the rankings provided by each MCDM method. Sensitivity analysis demonstrated that all investigated compromise candidate rankings show high convergence with the rankings provided by the particular MCDM methods. Thus, the performed study proved that the proposed approach shows high potential to be successfully used as a central component of DSS for recommending the most suitable product. Such DSS could be a universal and future-proof solution for e-commerce sites and websites, providing advanced product comparison capabilities in delivering a recommendation to the user as a final ranking of alternatives.

KEY SECTORS PERSPECTIVE IN SELECTING OPTIMAL BIOLOGICAL NUTRIENT REMOVAL TECHNOLOGIES FOR SEWAGE TREATMENT IN THE PHILIPPINES

The current effluent standards emphasize on the removal of nutrients from sewage, and one solution is for establishments to install biological nutrient removal (BNR) technologies. However, there are several factors to be considered in installing or upgrading the technologies. Hence, the study utilizes two multi-criteria decision analysis (MCDA) tools to determine the important attributes and the optimal technology from the perspective of the academe, regulatory agency, and industry. Calibrated fuzzy analytical hierarchy process (FAHP) calculates the relative importance of the three criteria (implementability, financial, and socio-environmental) and twelve sub-criteria. On the other hand, the grey relational analysis is used to calculate the performance of the four selected alternatives: 3-stage Bardenpho (A2O), 5-stage Bardenpho (5BP), sequencing batch reactor (SBR), and membrane bioreactor (MBR). Combining the results of calibrated FAHP and GRA provided the overall ranking of alternatives. Results showed that each sector prioritized different factors in the selection of the optimal BNR technology. The academe considers socio-environmental (0.43) as the most preferred criterion, while the regulatory agency and industry consider financial (0.36) and implementability (0.57), respectively. Overall, the three sectors agreed that the sequential batch reactor (SBR) is the optimal BNR technology (GRG = 0.69 - 0.79).

Multifuzzy Cubic Sets and Their Correlation Coefficients for Multicriteria Group Decision-Making

The notion of multifuzzy sets (MFSs) or multi-interval-valued fuzzy sets (MIVFSs) provides a new method to represent some problems with a sequence of the different and/or same fuzzy/interval-valued fuzzy membership values of an element to the set. Then, a fuzzy cubic set (FCS) consists of a certain part (a fuzzy value) and an uncertain part (an interval-valued fuzzy value) but cannot represent hybrid information of both MFS and MIVFS. To adequately depict the opinion of several experts/decision-makers by using a union/sequence of the different and/or same fuzzy cubic values for an object assessed in group decision-making (GDM) problems, this paper proposes a multifuzzy cubic set (MFCS) notion as the conceptual extension of FCS to express the hybrid information of both MFS and MIVFS in the fuzzy setting of both uncertainty and certainty. Then, we propose three correlation coefficients of MFCSs and then introduce correlation coefficients of MFSs and MIVFSs as special cases of the three correlation coefficients of MFCSs. Further, the multicriteria GDM methods using three weighted correlation coefficients of MFCSs are developed under the environment of MFCSs, which contains the MFS and MIVFS GDM methods. Lastly, these multicriteria GDM methods are applied in an illustrative example on the selection problem of equipment suppliers; then their decision results and comparative analysis indicate that the developed GDM methods are more practicable and effective and reflect that either different correlation coefficients or different information expressions can also impact on the ranking of alternatives. Therefore, this study indicates the main contribution of the multifuzzy cubic information expression, correlation coefficients, and GDM methods in the multifuzzy setting of both uncertainty and certainty.