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Mathematical Model and Solution for Land-Use Crop Planning with Cooperative Work

机译：合作开展土地利用作物规划的数学模型和解决方案

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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.
机译：如果忽略合作工作和其他特定限制，大多数针对土地利用农作物（如甘蔗）的农场工作计划都属于灵活的流水作业计划。由于传统的灵活流水车间调度方法无法制定这些特定的约束条件，因此我们需要一种新的方法来解决考虑合作工作的土地利用农作物计划问题。本文描述了一个详细的数学模型和一种用于求解该模型的混合算法，其中考虑了许多实际约束，包括协同工作，最佳时间窗口，两次操作之间的等待时间以及移动时间。混合算法在Gurobi中使用元启发式模拟退火和混合整数规划求解器。为了在合理的时间内获得良好的计划，我们采用了在模拟退火过程中固定部分工作顺序并使用求解器优化部分计划的策略。评估计算结果表明，该模型在实际约束条件下是可行的，并且该混合算法适用于调度计算。固定部分工作顺序的策略适用于减少大型土地利用作物计划问题的计算时间。

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