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中文摘要：
基于多目标进化算法的机器人路径规划问题存在求解速度慢的不足，为提高求解效率，提出了一种多目标二次优化方法（MOQO）。在MOQO方法中首先引入二次优化的思想，通过离线的全局优化为在线的局部优化提供一个次优的初始解集，以更有效利用全局优化过程的先验信息和进化信息，从而加速后期的局部优化操作；其次，在MOQO方法中还提出了一种改进的多目标进化算法PPMOEA，以进一步提高优化求解的实时性能。最终的机器人路径规划仿真实验测试了MOQO方法对进化求解操作的加速效果，证明了方法的有效性和可行性。
英文摘要：
A method named Multi - objective Quadratic Optimization （ MOQO ） is proposed for robot path - plan- ning to raise the computation efficiency of the former multi - objective evolutionary algorithm. Firstly, a quadratic optimization idea is introduced into MOQO, namely, through an offfine global optimization process to provide a subopti- mal initial solution set for the online local optimization process, thus using the apriori knowledge and evolutionary in- formation in the former optimization process more effectively, and accelerating later the local optimization process. Secondly, a modified multi -objective evolutionary algorithm is proposed in MOQO to improve the real -time per- formance of optimization process. Lastly, the simulations and trials show that the MOQO can accelerate the evolution- ary operation process effectively, and the feasibility and validation of MOQO are confirmed.
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