| 摘要: |
| 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。 |
| 关键词: 生物地理学算法 番茄 均衡供应 最优种植规划 |
| DOI：10.11841/j.issn.1007-4333.2015.01.023 |
| 投稿时间：2014-04-07 |
| 基金项目:国家自然科学基金资助项目 (61064005); 自治区研究生科研创新项目(XJGRI2014039) |
|
| Tomato planting planning research based on hybrid Biogeography-based optimization algorithm |
|
LUO Dan, ZHANG Hong-li
|
| (College of Electrical Engineering, Xinjiang University, Urumqi 830047, China) |
| Abstract: |
| To solve the imbalance supply of tomato sauce production materials,Hybrid Biogeography-Based Optimization was proposed to solve tomato planting decision problem by constructing nonlinear mathematical optimization model.Some strategies such as cosine migration model,disturb migration operator,mutation operator based on Gaussian distribution and the reasonable combination of mutation operator of differential evolution algorithm were used to improve the performance of biogeography-based optimization algorithm.A research was conducted in a Xinjiang Ketchup factory showed that the algorithm could realize the balance between tomato raw material supply and Ketchup factory capacity.Simulation results verified the rationality of the mathematical model for the tomato planting planning and the feasibility of the algorithm.The optimal cultivation scheme was derived and was compared with other intelligent optimization algorithms.The result of the algorithm showed good convergence. |
| Key words: Biogeography-Based Optimization tomato balanced supply the optimum planting planning |
