The problem of convergence and diversity in the course of population evolution is difficult to be balanced for solving the many‐objective optimization problem (MaOP). To track with the problem, a many‐objective optimization algorithm is designed. In the algorithm, a hybrid selection mechanism under the concurrent integration strategy is built to improve algorithm performance by employing the different selection operators. The concurrent integration strategy can select the suitable operator to balance the convergence and diversity of the solution in the course of the population evolutionary. To verify the effectiveness of the algorithm, the designed algorithm is compared with other five excellent many‐objective algorithms on DTLZ and WFG test problem. What is more, the designed algorithm is applied to solve the coal green production optimization problem. The simulation results show that the performance of designed algorithm is superior to whether the DTLZ and WFG test problem or the application problem.

中文翻译：

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煤绿色生产问题的混合多目标优化算法

人口演化过程中的收敛性和多样性问题很难解决多目标优化问题（MaOP）。为了跟踪该问题，设计了一个多目标优化算法。该算法建立了并发集成策略下的混合选择机制，通过采用不同的选择算子来提高算法性能。并发整合策略可以选择合适的算子，以在种群演化过程中平衡解决方案的收敛性和多样性。为了验证算法的有效性，将设计的算法与其他五种优秀的多目标算法在DTLZ和WFG测试问题上进行了比较。更，将设计的算法应用于解决煤绿色生产优化问题。仿真结果表明，所设计的算法的性能优于DTLZ和WFG测试问题还是应用问题。