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As world economic activities intensify and trade barriers fall, the formation of viable strategic alliances in the liner shipping industry gains importance and accelerates of necessity. However, the selection of a suitable partner for strategic alliance is not an easy decision, involving a host of complex considerations. Decision-making information is hard to come by and often vague, particularly regarding privately held companies. Fuzzy set theory was designed to sort through the uncertainties of vague linguistic terms and help generate a single possible outcome. This research paper proposes the utilization of the fundamental principles encompassed in the fuzzy set theory to analyze and consider a multiplicity of complex criteria and determines the most suitable partner in strategic shipping alliances. The fundamental emphasis of the current fuzzy multiple criteria decision-making (FMCDM) methodology is the determination, definition, testing and comparison of complex multi-level criteria used in the partnership selection process. The tools and formulas employed are: (1) triangular fuzzy numbers and linguistic values characterized by triangular fuzzy numbers which are used to evaluate the preference rating system; (2) the method of graded mean integration, and the entropy weighting method which are jointly used to adjust integration weights of all sub-criteria above those of the alternatives; (3) the concepts of ideal and anti-ideal solutions which are employed to calculate the relative closeness of the various alternatives versus ideal solutions to rank their priorities, and finally, to determine the best alternative. We design a hypothetical problem in selecting partners of strategic alliances for liner shipping to demonstrate the computational process of this FMCDM algorithm. The main contribution of this paper is that the definition, conversion, and treatment of vague and complex multi-level criteria as set memberships under the fuzzy set theory are employed to develop a practical model for business purpose.