Abstract:

To study the performance and application prospects of novel intelligent optimization algorithms， six bionic intelligent optimization algorithms proposed in the past few years were analyzed， concluding Harris Hawks Optimization （HHO） algorithm， Equilibrium Optimizer （EO）， Marine Predators Algorithm （MPA）， Political Optimizer （PO）， Slime Mould Algorithm （SMA）， and Heap-Based Optimizer （HBO）. Their performance and applications in different constrained engineering optimization problems were compared and analyzed. Firstly， the basic principles of six optimization algorithms were introduced. Secondly， the optimization tests were performed on ten standard benchmark functions for six optimization algorithms. Thirdly， six optimization algorithms were applied to solve three engineering optimization problems with constraints. Experimental results show that the convergence accuracy of PO is the best for the optimization of unimodal and multimodal test functions and can reach the theoretical optimal value zero many times. The EO and MPA are better for solving constrained engineering problems with fast optimization speed， high stability and standard deviation of a small order of magnitude. Finally， the improvement methods and development potentials of six optimization algorithms were analyzed.

Key words: Harris Hawks Optimization (HHO) algorithm, Equilibrium Optimizer (EO), Marine Predators Algorithm (MPA), Political Optimizer (PO), Slime Mould Algorithm (SMA), Heap-Based Optimizer (HBO), constrained engineering problem

摘要：

为了研究新型智能优化算法的性能和应用前景，选择了近几年提出的6种仿生智能优化算法：哈里斯鹰优化（HHO）算法、平衡优化（EO）算法、海洋捕食者算法（MPA）、政治优化（PO）算法、黏液霉菌算法（SMA）和堆阵优化（HBO）算法，对其性能和在不同带约束的工程优化问题上的应用进行对比分析。首先，对6种优化算法的基本原理进行介绍；然后，用6种优化算法对10个基准测试函数进行寻优测试；接着，将6种优化算法用于求解3种带约束的工程优化问题。实验结果表明，对于单峰和多峰测试函数的寻优，PO的收敛精度最佳，能够多次达到理论最优值0，且收敛速度较快；对于求解工程约束问题，EO和MPA较好，因为的标准差的数量级较小，且寻优速度较快，稳定性高。最后，分析了6种优化算法的改进方法及其发展潜力。

关键词: 哈里斯鹰优化算法, 平衡优化算法, 海洋捕食者算法, 政治优化算法, 黏液霉菌算法, 堆阵优化算法, 工程约束问题