【Objective】To address the imbalance in weight–volume resource utilization and the difficulty of coordinating vehicle loading and outsourcing decisions in multi-type vehicle transportation, a multi-type vehicle loading optimization method considering outsourcing is proposed.【Method】Cargo items are represented as two-dimensional weight–volume vectors, and a total-cost-minimization model is established. A genetic algorithm–dynamic volume–weight ratio decoding algorithm is proposed. The outer layer uses binary chromosomes to search for in-house and outsourced transportation decisions, while the inner layer constructs vehicle activation and cargo loading schemes according to vehicle operating costs and dynamic volume–weight ratios.【Result】For random instances with = 10, 20, and 30, the algorithm yields solutions with relative deviations of no more than 0.84% from the Gurobi optimal solutions, and the result for = 10 coincides with the Gurobi optimal solution. In the enterprise case, allowing outsourcing reduces the total cost by 14.67% and decreases the number of activated vehicles from 13 to 5.【Conclusion】The proposed algorithm coordinates in-house loading and outsourcing decisions, improves vehicle resource allocation efficiency, and supports transportation cost reduction and operational decision-making.