An implementation of the genetic algorithm in a design support tool for (large) solar hot water systems is described. The tool calculates the yield and the costs of solar hot water systems based on technical and financial data of the system components. The genetic algorithm allows for optimisation of separate variables such as the collector type, the number of collectors, the heat storage mass and the collector heat exchanger area. Optimisation can be focussed on, for example, payback time and CO2 emission reduction. Constraints such as maximum initial costs and installation space are taken into account. The applicability of the genetic algorithm was tested for optimisation of large solar hot water systems. Among others, the sensitivity of the optimum system design to the tap water draw-off and the draw-off pattern has been determined using the optimisation algorithm. As the genetic algorithm is a discrete optimisation tool and is implemented in the design tool through the use of databases, the number of variables in principle is free of choice.