Site Layout and Construction Plan Optimization Using an Integrated Genetic Algorithm Simulation Framework

Abstract

Efficiency of a planned site layout is essential for the successful completion of construction projects. Despite considerable research undertaken for optimizing construction site layouts, most models developed for this purpose have neglected the mutual impacts of the site layout and construction operation variables and are unable to thoroughly model these impacts. This paper outlines a framework enabling planners to anticipate site layout variables (i.e., size, location, and orientation of temporary facilities) and construction plan variables (e.g., resources and material delivery plan), and simultaneously optimize them in an integrated model. In this framework, genetic algorithm (GA) and simulation are integrated; GA heuristically searches for the near-optimum solution with minimum costs by generating feasible candidate solutions, and simulation mimics construction processes and measures the project costs by adopting those candidate solutions. The contribution of this framework is the ability to capture the mutual impacts of site layout and construction plans in a unified simulation model and optimize their variables in GA, which subsequently entails developing a more efficient and realistic plan. Applicability of the framework is presented in a steel erection project.