| 蚁群算法在啤酒发酵控制优化中的应用 |
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| 引用本文： | 肖杰,周泽魁. 蚁群算法在啤酒发酵控制优化中的应用[J]. 信息与控制, 2004, 33(4): 508-512 |
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| 作者姓名： | 肖杰 周泽魁 |
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| 作者单位： | 浙江大学控制系,浙江,杭州,310027 |
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| 摘 要： | 利用蚁群算法在啤酒发酵过程动力学模型的基础上对过程进行优化。在固定的发酵时间内，利用蚁群算法得到一系列不同的温度曲线，从中找出一条最优的温度曲线，使得发酵过程最后酒精量达到最大，同时保证副产品浓度最低，而且啤酒没有因为发酵温度过高而变质．仿真结果表明：利用蚁群算法对发酵过程进行优化，在较短的时间内就可以达到很好的优化效果．
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| 关 键 词： | 啤酒发酵 动力学模型 蚁群系统算法 优化 最优温度曲线 |
| 文章编号： | 1002-0411(2004)04-0508-05 |
Application of Ant Colony Algorithm to the Optimization of Beer Fermentation Control |
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| XIAO Jie,ZHOU Ze kui. Application of Ant Colony Algorithm to the Optimization of Beer Fermentation Control[J]. Information and Control, 2004, 33(4): 508-512 |
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| Authors: | XIAO Jie ZHOU Ze kui |
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| Abstract: | On the basis of the kinetic model of beer fermentation process, ant colony system algorithm is applied to optimize the process. During a fixed period of fermentation time, a series of different temperature profiles of the mixture are constructed, and an optimal one is chosen at last. The optimal temperature profile maximizes the final ethanol production and minimizes the byproducts concentration and spoilage risk. Simulation results show that using ant colony system algorithm to optimize the process, we can get satisfactory results without much computation effort. |
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| Keywords: | beer fermentation kinetic model ant colony system(ACS) algorithm optimization optimal temperature profile |
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