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Orvik, C P and Albrechtsen, E (2026) The mismatch between conceptualization and measurements of safety performance: insights from a qualitative study of the Norwegian construction industry. Construction Management and Economics, 44(05), 319–36.

Righetto, E, Micelli, E and Pellegrino, M (2026) Can the deep retrofit of the housing stock cost less? Learning curves and the costs of off-site industrialised construction in France. Construction Management and Economics, 44(05), 359–80.

Salah, M, Motawa, I and Elnabwy, M T (2026) Enhancing construction site layout planning using hybrid Ant Colony and simulated annealing algorithms. Construction Management and Economics, 44(05), 381–96.

  • Type: Journal Article
  • Keywords: Site layout planning; construction sites; Ant Colony Optimization (ACO); simulated annealing (SA); hybrid metaheuristics; construction management practices;
  • ISBN/ISSN: 0144-6193
  • URL: https://doi.org/10.1080/01446193.2026.2643612
  • Abstract:
    Effective construction site layout planning (CSLP) is critical for enhancing logistics efficiency, safety, and space utilization in complex construction environments. In practice, planners must evaluate multiple layout alternatives under spatial, operational, and safety constraints within limited decision time. However, traditional optimization approaches often struggle with the nonlinear and constraint-rich nature of real construction sites, either requiring excessive computational time or compromising solution quality. To address these challenges, this study proposes a hybrid metaheuristic framework that integrates Ant Colony Optimization (ACO) with Simulated Annealing (SA) to support CSLP decision-making. The approach leverages the global search capability of ACO and the local refinement strength of SA to generate high-quality layout solutions with improved computational efficiency. The hybrid mechanism employs adaptive pheromone updating alongside local search enhancement to balance exploration and exploitation effectively. The framework is validated through application cases, including a benchmark problem and a large-scale multi-building construction site. Results demonstrate that the proposed method achieves up to a 95% reduction in computational time compared with standalone approaches, while maintaining or improving solution quality. Beyond algorithmic performance, the study offers managerial value by enabling structured comparison of layout alternatives and supporting data-driven decision-making.

Yap, J B H, Tan, Z Y, Skitmore, M, Loo, S C and Yong, F Y Y (2026) Unmasking green procurement: What drives adoption in developing-country construction?. Construction Management and Economics, 44(05), 337–58.