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

TLDR

The paper proposes a combined compromise decision‑making algorithm and aims to demonstrate its advantages over existing methods. The method uses a grey‑relational distance measure, assigns weights via three equations, and applies an aggregated multiplication rule to rank alternatives. In a French logistics case, the algorithm outperforms existing methods and passes sensitivity analysis, confirming its effectiveness and unique structure.

Abstract

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.