A Hybrid Genetic Algorithm and Tabu Search for Construction Site Layout Planning Problem

Abstract

The construction site layout is widely acknowledged as a complex challenge in the field of construction management. However, it is crucial for nearly all construction projects, as the layout of site facilities can significantly impact on the project costs. This issue can be formulated as a Quadratic Assignment Problem, which is widely recognized to be NP-hard problem. While numerous methods have been proposed, most existing approaches either lack sufficient global search capabilities or struggle to escape local optima, leading to suboptimal solutions. To address these limitations, this study proposes a hybrid GA-Tabu algorithm that integrates the exploration strength of Genetic Algorithms with the exploitation efficiency of Tabu Search. This integration aims to achieve a better balance between global and local search processes, thereby enhancing the overall solution quality for the CSLP problem. The proposed algorithm has been subsequently tested with three case studies previously utilized in related research, effectively demonstrating its performance and applicability.