This invention belongs to the field of industrial manufacturing and resource optimization technology, specifically involving a
smart material batching optimization method for iron towers based on a two-layer genetic
ant colony
algorithm. The method includes: first, acquiring the parameters of raw materials and components for the iron
tower; grouping them according to material specifications to construct a material batching
optimization problem; generating an initial
population using multi-strategy greedy initialization; generating preliminary solutions by combining
pheromone guidance and
heuristic information from the
ant colony
algorithm; then completing
genetic evolution through elite retention, tournament selection,
crossover, and multi-strategy
mutation; and finally forming a two-layer collaborative optimization framework through constraint repair and
pheromone updating, ultimately outputting the optimal material batching scheme. This invention combines global
ant colony search with local genetic optimization, effectively overcoming the shortcomings of single algorithms such as being prone to getting trapped in local optima,
slow convergence, and
premature convergence. It can significantly improve
raw material utilization, reduce surplus material and the number of material units used, and is more robust and efficient in multi-material, multi-specification iron
tower batching scenarios. Compared with traditional methods, material utilization is greatly improved, effectively reducing enterprise production costs and providing reliable
technical support for the intelligent upgrading and efficient
resource utilization of iron
tower manufacturing.