Sugarcane-farming corporations manage large-scale farmlands, labor, and machinery. To efficiently manage daily operations, a systematic and detailed scheduling system is needed. Compared with other common scheduling problems, the sugarcane-farming scheduling problem presents some specific characteristics, such as cooperative work and uncertainty. By analyzing the practical constraints, we propose a new mathematical model and a hybrid approach to solve the scheduling problem of sugarcane-farming corporations. The approach comprises a meta-heuristics simulated annealing (SA) and a mixed integer programming (MIP) solver of the GNU linear programming kit. The SA algorithm is used for resource assignment and search control, whereas the MIP solver is used to acquire the optimal solution for resource assignment. For planning the farm works on large-scale-dispersed farmlands in the sugarcane-farming corporations, the hybrid approach is competent to mathematically calculate an optimal schedule with minimum completion time; this was explored from enormous candidate farm work permutations and resource combinations. The results demonstrate that the proposed hybrid approach can determine an optimal resource assignment and farm work schedule for a small-scale problem. The proposed approach is applicable to the construction of a long-term detailed scheduling system for sugarcane-farming corporations.