In recent years there has been a growing trend in major projects towards considering the whole project life cycle and it's costs. This analysis initially considered concept to commissioning, although more recently it has been expanded to consider concept to decommissioning. Within this project life cycle optimisations are performed to obtain efficient solutions. However, contemporary optimisation techniques still tend to focus on improving the performance of small subsystems within the project as a whole. An optimisation of the whole project across the entire project life cycle is not normally carried out. This thesis therefore proposes a general methodology for such a global optimisation model, which will allow the whole project to be considered within a single optimisation. The strategy consists of a basic scheme for input of all the project data to an objective function, as well as the definition of its constraints. The objective function can map to a value relating to cost, time, performance or risk. This allows the most important criteria to be maximised, as well as constraining other important criteria. The validity of the model is tested by applying it to the resource constrained project scheduling problem. This involves solving scheduling and resource allocation problems. In a large construction project these problems would be a subsystem of the global project model. By testing the global approach to optimisation on this problem using a genetic algorithm, and comparing it to locally optimising techniques, optimisation performance is shown to be improved by applying the global approach. Finally, the global approach is successfully applied to a case study. The results of both the case study and the simple problems demonstrate the global approach to be both feasible and advantageous for large construction projects.