The railway distribution company Green Cargo controls 80% of the Swedish market for rail transportation of goods. The subsidiary company Road & Logistics offers intermodal haulage solutions consisting of railway and trucks. The railway is used for the long distance haulage and the trucks for the shorter distances. During transportation, goods are re-consolidated as one unit in cross docking terminals to optimise the utilisation, which furthermore benefits the environment and also cut costs. The growing complexity in the distribution net has inevitably lead to a need of analysing tools, for the ability to control the distribution system and identify bottlenecks and interruptions in the system. Simulation, with the software Planimate, is primary developed to analyse existing or imaginable systems and is therefore the first choice of Green Cargo. I have evaluated an existing simulation model to find out if it is possible to use the model to analyse needs of resources or the optimal use of them in a garment distribution net. The study is limited to region of Stockholm, which means that trucks are the only observed vehicles. Treated companies are H&M, KappAhl, Dressmann, Lindex and Fashionet. Fashionet is a portal and contains all the smaller boutiques within the network of Green Cargo distribution. A frame of references gives the reader a theoretical introduction and background. Furthermore, the thesis includes a situation analysis of the defined system, with the purpose to identify the key resources. The key resources are then used in the analytic part of the paper as fundamental requirements for what the model needs to fulfil the main purpose with the study. The conclusion of the study is that the model needs several technical modifications. The model is essentially developed for operative planning, but at the same time demanding and time-consuming to use. Therefor, a solution to shorten the planning time is to develop different scenarios, each representing a typical week in the distribution system. The user then compares the real situation with historical created scenarios. In this way the user doesn’t need to go through the processes of data collection, data feeding and simulation. An unexpected positive synergy effect of the study was that small code errors was tracked and corrected, in due to the careful verification of the model. In reality, creators do not prior detailed verifications of developed models, because of time constraints.