Although many methods for dealing with multi-objective optimisation (MOO) problems are available [Deb01] and successful applications have been reported [Coe01], the comparison between MOO methods applied to real-world problem was rarely carried out. This paper reports the comparison between MOO methods applied to a real-world problem, namely, the optimisation of a micro heat exchanger (muHEX). Two MOO methods, Dynamically Weighted Aggregation (DWA) proposed by Jin et al. [Jin01, Jin01b] and Non-dominated Sorting Genetic Algorithms (NSGA-II) proposed by Deb et al. [Deb00, Deb02], were used for the study. The commercial computational fluid dynamics (CFD) solver called CFD-ACE+(1) is used to evaluate fitness. We introduce how to interface the commercial solver with evolutionary computation (EC) and also report the necessary functionalities of the commercial solver to be used for the optimisation.