Application of Rao optimization algorithms and archive control mechanism for resource leveling problems in construction projects
Engineering Computations (Swansea, Wales), cilt.43, sa.5, 2026 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 43 Sayı: 5
- Basım Tarihi: 2026
- Doi Numarası: 10.1108/ec-07-2025-0813
- Dergi Adı: Engineering Computations (Swansea, Wales)
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, ABI/INFORM, Aerospace Database, Compendex, INSPEC, zbMATH, Academic Search Ultimate (EBSCO), Engineering Source (EBSCO), Materials Science & Engineering Collection (ProQuest), Pharma Collection (ProQuest), Technology Collection (ProQuest)
- Anahtar Kelimeler: Archive control mechanism, Project scheduling, Rao optimization algorithms, Resource leveling
- Karadeniz Teknik Üniversitesi Adresli: Evet
Özet
Purpose – This study aims to address the complexities of resource leveling in construction projects, particularly under conditions of fluctuating resource demands and limited availability. It introduces a novel approach combining Rao algorithms with an archive control mechanism to enhance the effectiveness of resource management. Design/methodology/approach – The proposed method integrates the simplicity and robustness of Rao algorithms with an archive control mechanism to solve the Resource Leveling Problem (RLP). The archive control mechanism maintains a diverse pool of high-quality solutions, enabling a broader and more effective exploration of the solution space. Comprehensive simulations and comparative analyses with established techniques were conducted to evaluate the performance of the proposed approach. Findings – Results demonstrate that the proposed method significantly improves resource allocation balance, reduces peak resource requirements, and minimizes overall project costs. The archive control mechanism plays a key role in preventing premature convergence and enhancing solution diversity, leading to more optimized project schedules. Originality/value – This research introduces a novel hybrid framework for resource leveling that leverages the efficiency of Rao algorithms and the diversity-preserving capabilities of an archive control mechanism. The approach is particularly valuable for more complex construction projects where traditional methods often face limitations in handling resource fluctuations and optimization complexity.