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4CaaSt is an advanced everything as a service (XaaS) cloud platform. A complex service in its value network can be composed of several products. There a service provider generates revenue from delivering a service to customers but also has to pay for third party cloud products that its service uses. Several price models can be applied to the 4CaaSt products that can take into consideration the actual usage of its customers. The contribution of this Thesis is as follows: identification of appropriate price models for 4CaaSt products, formalization of revenue, costs and profit in a complex service and support for the price discovery and analysis problem of products in the 4CaaSt cloud marketplace. The solution addresses to support deciders to achieve certain business model goals based on the optimization of the prices in the price model of their products. In addition the solution supports to analyze and visualize revenue and cost flow in the product constellation of a service that result at different pricings. The Business Model Simulator (BMS) Web application has been built therefore. The solution of the BMS to address the optimization task is through a meta-heuristic approach. Hence the BMS simulates optimal pricings according to objective functions through a genetic algorithm.