Well-designed packaging is intended to present a product in the best possible way, which would have a significant impact on sales improvement. Creating and finding the ideal design solution for packaging is an extremely complex process. Many characteristics of a packaging design can affect the level of customer satisfaction, where the different characteristics of the packaging tend to have a different significance. To make the problem more complex, the significance of characteristics of a packaging design is not the same for all customers. Therefore, creating and finding the ideal design solution for packaging often involves an evaluation of a number of variants, typically evaluated on the basis of multiple criteria, often with different significance. To provide an efficient approach for the selection of appropriate packaging, a framework for selecting the appropriate packaging design which meets customer preferences, based on the SWARA method and group decision making, is proposed. The usability and efficiency of the proposed framework is considered in the case of the selecting the appropriate packaging design for the wine of the autochthonous grape variety called Black Tamjanika. On the basis the considered examples, it can be concluded that SWARA method can be successfully used to solve many similar problems, and that in some cases may have some advantages over similar methods, such as AHP method or Conjoint Analysis. As an advantage of the proposed procedure can be mentioned a much smaller number of comparisons in pairs, compared with the AHP method, and much more comprehensible procedure for selecting the most acceptable alternative, compared with Conjoint Analysis. The proposed framework can also be easily adjusted to solve a significant number of MCDM problemsDOI: http://dx.doi.org/10.5755/j01.ee.26.2.8820

Until now, many different multiple criteria decision-making methods have been proposed for the facilitation of different business problems such as entrepreneurial. In this article, a new approach for selecting the most acceptable alternative is considered, which is based on the integration of weighted sum and weighted product approaches. The basic idea of the newly proposed approach is partly based on the multiobjective optimization by ratio analysis plus the full multiplicative form method, but also includes some features of the weighted aggregated sum product assessment and combined compromise solution methods. The proposed method is tested by using two illustrative examples that are related to the contractor and industrial robot selection. Additionally, to test its reliability, the obtained results are compared with the ones gained by using the multiple-criteria decision-making methods of the first and second generations. The proposed method predicts the application of a much simpler normalization procedure, involves four utility measures for defining the overall utility of alternatives, and enables a much easier ranking of them. The final conclusion is that the simple weighted sum product method is easy to use and contributes to the increasing of the reliability of decisions that are made. Therefore, the proposal uses a much simpler normalization procedure, i.e., four utility measures for determining the overall utility of alternatives, and allows a much easier ranking of alternatives.

The main goal of this paper is to propose a Multiple-Criteria Decision-Making (MCDM) approach that will facilitate decision-making in the field of logistics—i.e., in the selection of the optimal equipment for performing a logistics activity. For defining the objective weights of the criteria, the correlation coefficient and the standard deviation (CCSD method) are applied. Furthermore, for determining the semi-objective weights of the considered criteria, the indifference threshold-based attribute ratio analysis method (ITARA) is used. In this way, by combining these two methods, the weights of the criteria are determined with a higher degree of reliability. For the final ranking of the alternatives, the measurement of alternatives and ranking according to the compromise solution method (MARCOS) is utilized. For demonstrating the applicability of the proposed approach, an illustrative case study pointing to the selection of the best manual stacker for a small warehouse is performed. The final results are compared with the ones obtained using the other proved MCDM methods that confirmed the reliability and stability of the proposed approach. The proposed integrated approach shows itself as a suitable technique for applying in the process of logistics equipment selection, because it defines the most influential criteria and the optimal choice with regard to all of them in a relatively easy and comprehensive way. Additionally, conceiving the determination of the criteria with the combination of objective and semi-objective methods enables defining the objective weights concerning the attitudes of the involved decision-makers, which finally leads to more reliable results.

A correlation between fuzzy logic systems (FLS) and zeroing neural networks (ZNN) design is investigated. It is shown that the gain parameter included in ZNN design can be dynamically adjusted over time by means of an appropriate value derived as the output of a properly defined FLS, which includes appropriately defined membership functions and fuzzy logic rules. Dynamical systems which are applicable to time-varying rank-deficient matrices are proposed. Convergence properties are investigated and illustrative simulation experiments are performed. Presented simulation experiments confirm the superiority of the FLS proposed in this article with respect to previously proposed FLS for dynamic adjustment of gain parameters. Furthermore, the superiority of the FLS-based ZNN model over the corresponding ZNN models based on the classical approach in defining the varying-gain parameter is demonstrated.