Abstract:

Construction site layout planning (CSLP) has been recognized as a critical step in construction planning. The basic function of this process is to find the best arrangement of the temporary facilities according to multiple objectives that may conflicts with each other. Commonly considered objectives are layout cost and safety hazards. The problem is subjected to logical and resource constraints. The formulation of construction site layout planning model as an optimization problem turns out to be nonlinear programming problem where there are conflicting multi-objectives to be achieved. It is shown that the swarm intelligence based meta-heuristic algorithms are quite powerful in obtaining the solution of such hard to solve type of optimization problems. In this study a novel multi objective artificial bee colony (MOABC) via Levy Flights algorithm is proposed. The model takes in account the dynamic nature of the problem where the demand on temporary facilities is changing during various phases of the project life cycle and the presence of obstructions when determining travel distances. It allows the use of facilities of unequal area and the orthogonal rotation of temporary facilities. The performance of the proposed MOABC via levy flights algorithm is verified by solving mathematical benchmark problems, benchmark engineering design problems, and a benchmark CSLP problem. The comparison with most recent meta-heuristic algorithms demonstrated the robustness of the proposed algorithm. The model was also applied to optimize a CSLP problem for a real construction project of a private hospital in the Kingdom of Bahrain.