Advanced construction site layout planning for prefabricated projects: an application of the new algorithm

Purpose This study aims to optimize the construction site layout planning (CSLP) problem, with a focus on prefabricated projects. It proposes the use of the oMOAHA algorithm, an enhanced version of the multi-objective artificial hummingbird algorithm (MOAHA), to address challenges related to search space exploration and local optimization in CSLP. Design/methodology/approach The study integrates three techniques – opposition-based learning (OBL), quasi-opposition and quasi-reflection – into the initialization phase of the MOAHA algorithm, creating the oMOAHA variant. This model is applied to all three types of CSLP problems – pre-determined location, grid system and continuous space – to evaluate its effectiveness. Six objective functions (three related to cost, two to safety and one to tower crane efficiency) and four site-related constraints are considered through three case studies taken from previous research and one real project involving prefabricated steel structures. Findings The oMOAHA algorithm demonstrates superior performance compared to previous models, consistently outperforming traditional approaches in CSLP optimization for prefabricated projects. In the real case study, the proposed model exceeded the actual project plan by 28–43%, indicating its potential to significantly improve both solution quality and project outcomes. Originality/value This study is the first to apply an optimization model to all three types of CSLP problems – pre-determined location, grid system and continuous space – within a unified framework. The integration of advanced techniques into the MOAHA algorithm and the model’s successful application in a real prefabricated project underscore its high applicability and effectiveness in modern construction management.