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Critical success factors can be used in value management workshops to determine the client value system, which in turn is critically important to the briefing process and the successful delivery of construction projects. This research is concerned with international construction projects. In particular, it investigates the impact of local knowledge on the client value system. Workshops were organised on 12 international projects in the western Balkans region. The initial client value system was captured by using a paired comparison exercise. Next, local knowledge information was introduced, and the EFTE (Estimate-Feedback-Talk-Estimate) technique was used to capture the revised client value system. The changes in the two sets of client value systems were analysed. The results indicate that 4 parameters (Scope, Contract-admin, Human resources and Health and Safety) out of 8 changed and that the changes were statistically significant. Local knowledge can be used to impact client value system.

In this paper, an original modification of the generalised robust estimation of deformation from observation differences (GREDOD) method is presented with the application of two evolutionary optimisation algorithms, the genetic algorithm (GA) and generalised particle swarm optimisation (GPSO), in the procedure of robust estimation of the displacement vector. The iterative reweighted least-squares (IRLS) method is traditionally used to perform robust estimation of the displacement vector, i.e., to determine the optimal datum solution of the displacement vector. In order to overcome the main flaw of the IRLS method, namely, the inability to determine the global optimal datum solution of the displacement vector if displaced points appear in the set of datum network points, the application of the GA and GPSO algorithms, which are powerful global optimisation techniques, is proposed for the robust estimation of the displacement vector. A thorough and comprehensive experimental analysis of the proposed modification of the GREDOD method was conducted based on Monte Carlo simulations with the application of the mean success rate (MSR). A comparative analysis of the traditional approach using IRLS, the proposed modification based on the GA and GPSO algorithms and one recent modification of the iterative weighted similarity transformation (IWST) method based on evolutionary optimisation techniques is also presented. The obtained results confirmed the quality and practical usefulness of the presented modification of the GREDOD method, since it increased the overall efficiency by about 18% and can provide more reliable results for projects dealing with the deformation analysis of engineering facilities and parts of the Earth’s crust surface.

Discusses a solution to a growing need for Industry Knowledge Base in the construction industry. This paper shows a Case Based Reasoning model based on the Rough Sets Theory and applied as a decision support in the preliminary design phase of construction projects.