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中文摘要：
复杂系统可靠性优化问题是一类有约束限制且目标函数具有多个局部极值的非线性优化问题.为求解该类问题,提出了一种混合万有引力搜索算法的求解方法.算法利用基于万有引力定律的寻优机制指导群体进行全局搜索,并采用序列二次规划算法进行局部搜索,避免基本万有引力搜索算法陷入局部最优,改善优化性能,加快寻优速度.通过实例计算,并与蚁群优化算法、微粒群算法、蜂群算法和基本万有引力搜索算法等进行比较,验证了算法的可行性和有效性.
英文摘要：
Reliability optimization problem of complex system is a nonlinear optimization problem under the constraint conditions and in the case of that the objective function has a large number of local extreme values. Hybrid gravitational search algorithm was proposed to solve the model. In the algorithm, a searching mechanism based on the law of gravitation was used to find the global optimal solution. Sequential quadratic programming was employed as a local search method to avoid being trapped into local optimum in the basic gravitational search algorithm. The optimization performance is improved and the search speed is accelerated in the proposed algorithm. Computations on some pratical examples and comparisons with ant colony optirnization algorithm. particle swarm optimization algorithm, artificial bee colony algorithm and basic gravitational search algorithm demonstrate the algorithm is feasible and effective.
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