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为解决番茄酱产季原料供应不均衡问题,在构建番茄种植规划的数学模型基础上,提出采用生物地理学算法对番茄种植规划模型的求解。利用余弦迁移模型、干扰迁移算子和基于高斯分布的变异算子对BBO算法进行适当改进,并与差分进化算法的变异算子结合,以增强生物地理学算法的全局搜索性能。以新疆某番茄酱厂为例对番茄种植规划问题进行计算,结果表明:采用该算法获得的种植方案能实现番茄原料产量与番茄酱厂生产能力之间的平衡。仿真结果验证了番茄种植规划数学模型的合理性。在求解番茄种植规划问题上,与其他智能优化算法相比,该算法具有较好的收敛性。
In order to solve the problem of unbalanced supply of raw material of tomato pasteurization, based on the mathematical model of tomato plantation planning, this paper proposed the solution of tomato plantation planning model by biogeography algorithm. The BBO algorithm is modified with cosine migration model, interference migration operator and mutation operator based on Gaussian distribution, and combined with the mutation operator of differential evolution algorithm to enhance the global search performance of the biogeography algorithm. Taking a ketchup factory in Xinjiang as an example, the tomato planting planning problem was calculated. The results showed that the planting scheme obtained by this algorithm could achieve the balance between the yield of tomato and the production capacity of tomato sauce factory. The simulation results verify the rationality of mathematical model of tomato plantation planning. Compared with other intelligent optimization algorithms, this algorithm has better convergence in solving tomato planting planning problem.