针对传统多目标灰狼优化算法易出现局部最优和稳定性差的问题，提出了一种改进的多目标灰狼算法。引入基于顺序查找策略（ENS）的非支配排序方法提高算法的速率，采用基于参考点的选取策略以均衡算法优化结果分布，并通过模拟二进制交叉进化机制改善算法跳出局部最优解的能力。结合多目标算法的评价指标，开展基准函数仿真试验，验证了改进算法的优越性和有效性。将改进算法应用于电厂多目标负荷优化分配中，优化结果表明，改进灰狼算法可以有效解决电厂的多目标优化分配问题。

Aiming at the issues of local optimum and poor stability of traditional multiobjective grey wolf algorithm, this study proposed a modified multiobjective grey wolf algorithm,which introduced the ENSbased nondominated sorting method to improve the speed of the algorithm, adopted the selection strategybased on reference points to balance algorithm and optimize the distribution of results, and simulated the binary crossover evolution mechanism to improve the ability of the algorithm to jump out of local optimum solution.Combined with the evaluation index of the multiobjective algorithm, the benchmark function simulation experiment was carried out to verify the superiority and effectiveness of the modified algorithm. The modified algorithm is applied to the multiobjective optimal load distribution of thermal power plants, the optimization results indicate that the modified grey wolf algorithm can effectively solve the problems of the multiobjective optimal load distribution of thermal power plants.

TM62