Aiming at the supply chain path optimization problem of manufacturing enterprises, this paper constructs a multi-objective model based on the total cost of supply chain and carbon emission. Based on the traditional ant colony algorithm, the hybrid ant colony algorithm incorporates the uniparental genetic algorithm to improve the convergence speed of the algorithm and save computing resources. The example experiment verifies that the uniparental genetic hybrid ant colony algorithm outperforms the basic ant colony algorithm and the chaotic ant colony algorithm. A residential construction enterprise project in X province is selected as the research object, and the uniparental genetic hybrid ant colony algorithm is used to realize the multi-objective optimization of assembly building supply chain cost-carbon emission. The optimal total cost and carbon emission of the supply chain solved by this paper’s method are 1196101 yuan and 252721 kgCO2 respectively, which are better than that of the chaotic ant colony algorithm. The optimization of the assembly building supply chain with both economic and environmental benefits is realized, which provides decision-making guidance for the production plan of assembly building supply chain.
