Outsourcing with multiple subcontractors is a major operational management challenge for today’s manufacturing firms. The joint decision-making between outsourcing options and in-house scheduling is crucial to the cost reduction and efficiency increase of these firms. To jointly optimize single-machine batch scheduling with multiple subcontractors available for job outsourcing, this study constructs a 0-1 integer programming model, the objective of which is to minimize the sum of total outsourcing cost and total in-house batch processing cost under the premise that both the total outsourcing cost and the latest leading time for outsourcing jobs are subject to upper limits. An improved genetic algorithm and a greedy algorithm are also designed for joint optimization. The study takes the joint decision-making scenario of outsourcing and batch scheduling in a ceramic enterprise as an example and compares the solution performance of the two algorithms. The improved genetic algorithm shows its comparative advantages in terms of solution quality and efficiency. The results of a sensitivity experiment show that the latest leading time for outsourcing jobs has a significant impact on the total operating cost, while the upper limit of the total outsourcing cost does not significantly influence the total operating cost.