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Submitted
11 November 2025
Accepted
28 May 2026
Published
31 May 2026
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Abstract

Efficient management of the concrete supply chain is essential for minimizing project delays, reducing costs, and maintaining construction quality. However, the interdependence among batching plants, transportation fleets, and construction sites introduces nonlinear and dynamic challenges that make scheduling optimization highly complex. This study proposes the Artificial Satellite Search Algorithm (ASSA), a novel metaheuristic inspired by the orbital motion and trajectory control of artificial satellites, to optimize concrete material logistics in construction projects. ASSA models the exploration–exploitation process as a dynamic orbital adjustment, enabling adaptive transitions between global search and local refinement. The optimization aims to minimize total logistics cost and delivery delay while adhering to capacity and time constraints. Comparative experiments conducted using both benchmark datasets and real project conditions show that ASSA outperforms Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), achieving a 10.2% cost reduction and a 14.7% improvement in convergence speed. The results demonstrate that ASSA provides a robust and efficient alternative for optimizing material supply chain scheduling in construction management.

Keywords

Supply chain optimization Concrete materials Metaheuristic Construction management Artificial satellite search algorithm

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Copyright (c) 2026 Moh Nur Sholeh, Mochamad Agung Wibowo, Shifa Fauziyah

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How to Cite
Sholeh, M. N., Wibowo, M. A., & Fauziyah, S. (2026). Optimization of concrete material supply chain in construction projects using the artificial satellite search algorithm. Teknisia, 31(1), 65–73. https://doi.org/10.20885/teknisia.vol31.iss1.art6
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