董建军, 石博强, 张文明. ACO算法及其在铰接车辆优化设计中的应用[J]. 农业工程学报, 2011, 27(1): 186-190.
    引用本文: 董建军, 石博强, 张文明. ACO算法及其在铰接车辆优化设计中的应用[J]. 农业工程学报, 2011, 27(1): 186-190.
    Dong Jianjun, Shi Boqiang, Zhang Wenming. ACO algorithm and its application to optimization design of articulated vehicles[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2011, 27(1): 186-190.
    Citation: Dong Jianjun, Shi Boqiang, Zhang Wenming. ACO algorithm and its application to optimization design of articulated vehicles[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2011, 27(1): 186-190.

    ACO算法及其在铰接车辆优化设计中的应用

    ACO algorithm and its application to optimization design of articulated vehicles

    • 摘要: 为了缩短工程设计周期和提高产品的质量,针对协同优化(CO)算法存在的计算量大、协调困难等问题进行了改善性研究。改善后的协同优化(ACO)算法采取了无约束的系统级,排除了单一雅克比方程式问题,使用了L1范数改进了CO算法的学科一致性约束,另外子系统增加了一些优化参数和约束模型。通过算例验证,ACO算法在计算效率上比CO算法提高了2.6倍,优化结果也更加逼近标准解。最后,将ACO算法应用到铰接车辆设计中,车辆的燃油经济性提高了2.596%,车辆速度从零到最高车速所需要的时间也减少了6.051 s。该算法有助于提高复杂工程系统优化设计中计算的效率和准确性。

       

      Abstract: In order to shorten the design period of engineering systems and improve product quality, and according to computational complexity, coordination disorder and other problems existing in collaborative optimization (CO) algorithm, some ameliorated studies were done in the paper. The Ameliorated Collaboration Optimization (ACO) algorithm was applied unconstrained system level which eliminated the potential for a singular Jacobian, and L1 norm which was used for improving subsystem consistency constraint. In addition, some optimization parameters and constraint models were added in the subsystem. The results from numerical simulation showed that computing efficiency of ACO algorithm was 2.6 times of CO algorithm, and the optimization result was more approximate to the real datum. Furthermore, ACO algorithm was applied to the design of articulated vehicles, fuel economy for vehicle could be improved by 2.596%, and the acceleration time of vehicle from zero to maximum velocity decreased by 6.051 seconds. The results show that the algorithm can help to improve calculation efficiency and accuracy in the optimization design of complex engineering system.

       

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