Various optimization-based process synthesis approaches exist to propose a process structure and associated parameters, which have been applied on many applications. The goal of this work is to provide a comparison of methods on a common process synthesis problem.Three methods are compared on an identical test problem, they differ in the synthesis approach (based on a superstructure or generative without predefined structures), process modelling (equation-or simulator-based), optimization algorithms (global NLP, MINLP, evolutionary) and implementation (dedicated or commercial programs). Results especially highlight the importance of the search space definition, and the need for accurate process models during the synthesis step.