Abstract

Previous studies on construction site layout often simplified the site as a rectangle, with little consideration of adaptability to complex terrain and multiple functional constraints. An optimization method was developed for irregular construction sites, based on Systematic Layout Planning (SLP) and an improved Non-dominated Sorting Genetic Algorithm II (NSGA-II), to address the limited adaptability of traditional methods in multi-objective and multi-constraint scenarios. A mathematical model for site layout was constructed using a rasterization method, with transportation time, transportation cost, and noise level as the optimization objectives. High-quality initial populations were generated by quantifying logistics and non-logistics relationships using the SLP method. The NSGA-II algorithm was enhanced with an adaptive penalty function, two-point crossover encoding, dynamically adjusted crossover and mutation probabilities, and a population restart mechanism. This improved its global search efficiency and convergence performance in complex solution spaces. Case validation results indicate that SLP-INSGA-II outperforms NSGA-II and SLP-NSGA-II while maintaining comparable performance to INSGA-II on some indicators. Without degrading overall optimization performance, incorporating SLP-based engineering priors can enhance search guidance, leading to layout solutions that are both feasible and engineering-interpretable. This study provides a modeling and solution approach for layout optimization in irregular construction sites.

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