Mathematical model and solution for land-use crop planning with cooperative work

Most farm work planning for land-use crops such as sugarcane belongs to flexible flow shop scheduling if neglecting cooperative work and other specific constraints. Because the conventional approaches to the flexible flow shop scheduling cannot formulate these specific constraints, we require a new approach for solving land-use crop planning problems that considers cooperative work. This paper describes a detailed mathematical model and a hybrid algorithm for solving the model, in which many practical constraints are taken into account, including cooperative work, optimum time windows, waiting time between operations, and moving time. The hybrid algorithm uses meta-heuristic simulated annealing and a mixed integer programming solver in Gurobi. In order to obtain good schedules in a reasonable time, we adopt a strategy of fixing partial work sequences in the simulated annealing procedure and optimizing the partial schedule using the solver. The results of the evaluation computation show that the proposed model is operative for the practical constraints, and that the hybrid algorithm is adaptable to scheduling computation. The strategy of fixing partial work sequences is applicable to reducing computation times for large-sized land-use crop planning problems.