<![CDATA[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.]]>
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