A combined compromise solution (CoCoSo) method for multi-criteria decision-making problems

PurposeThe purpose of this paper is to discuss the advantage of a combinatory methodology presented in this study. The paper suggests that the comparison with results of previously developed methods is in high agreement.Design/methodology/approachThis paper introduces a combined compromise decision-making algorithm with the aid of some aggregation strategies. The authors have considered a distance measure, which originates from grey relational coefficient and targets to enhance the flexibility of the results. Hence, the weight of the alternatives is placed in the decision-making process with three equations. In the final stage, an aggregated multiplication rule is employed to release the ranking of the alternatives and end the decision process.FindingsThe authors described a real case of choosing logistics and transportation companies in France from a supply chain project. Some comparisons such as sensitivity analysis approach and comparing to other studies and methods provided to validate the performance of the proposed algorithm.Originality/valueThe algorithm has a unique structure among MCDM methods which is presented for the first time in this paper.

A Calibration-Free Method Based on Grey Relational Analysis for Heterogeneous Smartphones in Fingerprint-Based Indoor Positioning

The fingerprint method has been widely adopted in Wi-Fi indoor positioning because of its advantage in non-line-of-sight channels between access points (APs) and mobile users. However, the received signal strength (RSS) during the fingerprint positioning process generally varies due to the dissimilar hardware configurations of heterogeneous smartphones. This difference may degrade the accuracy of fingerprint matching between fingerprint and test data. Thus, this paper puts forward a fingerprint method based on grey relational analysis (GRA) to approach the challenge of heterogeneous smartphones and to improve positioning accuracy. Initially, the grey relational coefficient (GRC) between the RSS comparability sequence of each reference point (RP) and the RSS reference sequence of the test point (TP) is calculated. Subsequently, the grey relational degree (GRD) between each RP and TP is determined on the basis of GRC, and the K most relational RPs are selected in accordance with the value of GRD. Finally, the user location is determined by weighting the K most relational RPs that correspond to the coordinates. The main advantage of this GRA method is that it does not require device calibration when handling heterogeneous smartphone problems. We further carry out extensive experiments using heterogeneous Android smartphones in an office environment to verify the positioning performance of the proposed method. Experimental results indicate that the proposed method outperforms the existing ones no matter whether heterogeneous smartphones are used.

Software solution of medical grey relational method based on SAS environment

Purpose The purpose of this paper is to construct a new algorithm of program procedure for medical grey relational method based on SAS software. Design/methodology/approach Based on the SAS environment, the authors construct a new algorithm of program procedure through the following methods: the construction data set, confirmation of the comparison sequence and reference sequence, the original data transformation, calculation of the grey relational coefficient of reference sequence and comparison sequence and calculating the correlation. Findings The results show that the novel algorithm of program procedure for medical grey relational method based on SAS software satisfies the properties properly. It also fully confirmed the biggest advantage of the grey relational analysis is that its requirements are not too high for the amount of data, and it does not need to follow the typical distribution. Originality/value The paper succeeds in constructing a novel algorithm of program procedures for medical grey relational method and providing a valuable tool for solving similar problems.

Study on Grindability Evaluation of Ceramic Materials Based on Interval Gray Principal Component Analysis

A new comprehensive evaluation method for grindability of ceramic materials is advanced. The mechanical property parameters of ceramic materials are selected as influencing factors for grindability, the interval sample matrices are established, the interval grey relational coefficient matrices are calculated and the factors weights determined by the eigenvectors. The important degree sequence of influencing factors and comprehensive evaluation value of grindability for ceramic materials are obtained. Seven typical engineering ceramic materials are analyzed using the method, the objective and comprehensive results are gained.

Surface Image Local Contrast Enhancement Based on Texture Discrimination via Grey Relational Analysis

Based on the analysis of main texture information in the neighborhood of image, we use the grey relational coefficient to decide the most obvious texture direction, which is conductive to selectively increase the local contrast of surface image. Simulation results show that the algorithm can obtain better experimental results, and it is a good method worth continuing to study later.