A Multi-objective Optimization Model for Solving Construction Site Layout Planning Problem Considering Safety and Risk Criteria

This paper deals with construction site layout planning (CLSP) problem in the context of a multi-objective optimization model. According to the operational plans in Iran, in execution of the construction projects, special places are considered to accommodate the respective facilities in the jobsite. As an important part of project execution, the site layout planning has always been of concern for clients, contractors and consultants which is majorly intended to layout the facilities by properly arranging the them such as offices, warehouses, residences etc. such that materials, information and staff could be transferred optimally. Noteworthy, an appropriate layout improves level of safety and efficiency, reduces transport costs, prevents formation of bottlenecks and obstructions ahead of materials and equipment transfer particularly in mega projects. The site layout could be arranged with respect to the decision maker’s opinions based on different criteria. The model’s target functions include maximizing the safety level of construction facilities along with minimizing the corresponding costs and finally, minimizing the respective risks in potential areas. The constraints involve unique layout of each facility as well as the allowable distance between various facilities. Given the fact that the CSLP is classified as an NP-hard problem, it would be difficult to derive viable results using mathematical models whose solution process is time-taking as well. In this respect, to solve the numerical examples in a realistic representation scheme, NSGAII and MOGWO metaheuristic algorithms are applied. In order to compare efficiency of the proposed algorithms with the results derived from mathematical model solution, a number of standard measures have been used. The results indicate that the Pareto frontier produced by the proposed algorithms in numerical examples, is significantly in agreement with the optimal Pareto frontier in the case of small sizes approving great efficiency of the algorithms. Moreover, it was observed that in medium and large sizes, performance of the MOGWO surpasses that of NSGAII, making it appropriate for real-size cases. Lastly, results of this study could be considered as a management tool to make optimal strategic decisions aiming to develop the CSLP studies.