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针对带约束的高维非线性多目标优化问题,给出一种混合型的智能优化算法进行求解.在和声搜索算法搜索机制的基础上,通过吸收分枝定界的思想,加入了分散搜索算法的优化机制,由此改善了和声搜索算法求解多目标问题时效率不高、搜索方向有时盲目的不足,同时也增强了算法的全局搜索能力,丰富了解的多样性.算法在计算机上编程实现,并对DTLZ系列中的问题进行了求解测试,取得了在三目标问题下的Pareto最优面.通过解集的分散程度和间距等指标对结果进行了评估,并与已有算法的结果进行了对比,验证了所给算法在求解多目标优化问题上的优势.
Aiming at constrained high-dimensional nonlinear multi-objective optimization problem, a hybrid intelligent optimization algorithm is proposed to solve the problem.On the basis of the search mechanism of harmony search algorithm, by absorbing the idea of branch and bound, Optimization mechanism to improve the harmony search algorithm for solving multi-objective problems is not efficient, blind search sometimes blind enough, but also enhance the global search capabilities of the algorithm to enrich the understanding of the diversity of the algorithm programmed on the computer, The problems in DTLZ series are solved and tested, and the Pareto optimal surfaces under the three-objective problem are obtained.The results are evaluated by the dispersion degree and spacing of the solution sets, and the results are compared with the results of the existing algorithms In contrast, the advantages of the proposed algorithm in solving multi-objective optimization problems are verified.