基于约束一致策略的人工蜂群算法
Artificial Bee Colony Algorithm Based on Constrained Consistent Strategy
摘要: 在过去的研究中，进化算法逐渐被广泛应用于求解复杂优化问题。然而，利用进化算法解决约束优化问题时，常常不能得到很好的结果，因为它们不能直接减少约束问题的约束违反程度。为了能够更好地得到目标函数的最优解，且减少约束违反对最优解的影响，本文将人工蜂群算法(ABC)的全局优化优势和约束一致策略(CC)的稳定计算特性集成到一种新的混合启发式算法中——基于约束一致策略的人工蜂群算法(ABCCC)。在进化搜索过程中，约束一致策略对于快速减少约束违反是相当有效的。通过一组测试函数，以及基于约束一致策略的粒子群算法(PSOCC)和基于约束一致策略的差分进化算法(DECC)两种方法进行比较，证明ABCCC具有一定的处理约束优化问题的能力。实验结果表明，该算法在优化质量和收敛速度方面都具有良好的性能。
Abstract: Over the last few decades, evolutionary algorithms have been widely used to solve complex optimization problems. However, when using evolutionary algorithms to solve constraint optimization problems, best results are often not obtained, because they cannot directly reduce the degree of constraint violation. In order to obtain the better optimal solution of the objective function and reduce the impact of constraint violation on the optimal solution, this paper integrates the global op-timization advantages of the artificial bee colony algorithm (ABC) and the stable computing characteristics of the constraint consensus strategy (CC) into a new hybrid heuristic algorithm—the constraint consensus strategy based artificial bee colony algorithm (ABCCC). During the evolutionary search, the constraint consensus strategy is quite effective for rapidly reducing constraint violations. Through a set of test functions and a comparison between PSOCC and DECC, it is proved that ABCCC has certain ability to deal with constraint optimization problems. Experimental results show that the algorithm has good performance in optimizing quality and convergence speed.
文章引用：吴钰晗, 梁晓丹. 基于约束一致策略的人工蜂群算法[J]. 计算机科学与应用, 2020, 10(11): 2034-2048. https://doi.org/10.12677/CSA.2020.1011215

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