Improving Environmental Sustainability Design using Ant Colony Algorithm Systems

In the context of increasingly serious global environmental problems, how to achieve sustainable design has become an urgent challenge. This paper aims to use the ant colony algorithm (ACO) to improve the efficiency and effectiveness of environmental sustainable design. This paper first defines the design goals and constraints, and then constructs an optimization model based on the ant colony algorithm. By simulating the path selection of ants on the graph, multiple iterative steps are designed: initializing the ant colony, calculating heuristic information, updating pheromones, and selecting the optimal path. A case study of a construction project was conducted in practical application. By implementing the ant colony algorithm to optimize the design scheme, the efficiency of building material utilization can reach up to 92%. The ant colony algorithm has significant optimization potential in environmental sustainable design and can effectively promote the rational use of resources and environmental protection.