Purpose: The 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/approach: This 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.Findings: The 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/value: The algorithm has a unique structure among MCDM methods which is presented for the first time in this paper.

Evaluation based on Distance from Average Solution (EDAS) is a new multicriteria decision making (MCDM) method, which is based on the distances of alternatives from the average scores of attributes. Classical EDAS has been already extended by using ordinary fuzzy sets in case of vague and incomplete data. In this paper, we propose an interval-valued intuitionistic fuzzy EDAS method, which is based on the data belonging to membership, nonmembership, and hesitance degrees. A sensitivity analysis is also given to show how robust decisions are obtained through the proposed intuitionistic fuzzy EDAS. The proposed intuitionistic fuzzy EDAS method is applied to the evaluation of solid waste disposal site selection alternatives. The comparative and sensitivity analyses are also included.

This study provides a novel integrated multi-criteria decision-making approach to sustainable supplier selection problems. Despite the large supply chain management literature on green performance measurement, the need for a systematic analysis of how specific sustainable variables develop and affect each other remains mostly overlooked. The proposed integrated framework allows for such an analysis. By combining analytic network process and quality function deployment, our model identifies a clear hierarchical structure for all the relevant sustainable factors and sub-factors while weighting the decision criteria based on the importance given to customer requirements. Finally, suppliers are ranked using a multi-objective optimisation procedure based on ratio analysis and weighted aggregated sum product assessment. The proposed framework is used to analyse a case study of a dairy company, but it can be easily implemented for supplier selection by any other company with similar features.