中文摘要：

最近建议的杜鹃搜索算法基于概率是一个进化算法。它在解决多模式的不连续、非线性的问题超过另外的算法。因为执行随机的散步采用利维飞行，它做的搜索是很有效的。这份报纸为多客观的问题(IMOCS ) 建议杜鹃搜索的一个改进版本。与 nondominated 排序结合了，挤满距离和利维班机，精英统治策略被使用改进算法。然后数字的研究被进行把算法与演示作比较，对某基准测试的 NSGA-II 工作。结果证明我们的改进杜鹃很快寻找算法集中并且 efficienly 表现。

英文摘要：

The recently proposed Cuckoo search algorithm is an evolutionary algorithm based on probability. It surpasses other algorithms in solving the multi-modal discontinuous and nonlinear problems. Searches made by it are very efficient because it adopts Levy flight to carry out random walks. This paper proposes an improved version of cuckoo search for multi-objective problems（IMOCS）. Combined with nondominated sorting, crowding distance and Levy flights, elitism strategy is applied to improve the algorithm. Then numerical studies are conducted to compare the algorithm with DEMO and NSGA-II against some benchmark test functions. Result shows that our improved cuckoo search algorithm convergences rapidly and performs efficienly.