免疫禁忌混合智能优化算法在配电网检修优化中的应用

从配电网设备检修计划编制的实际需要出发，建立了考虑多种约束条件、以配电网经济性最好为目标的检修计划优化模型。针对该模型的特点，提出了一种充分结合免疫算法与禁忌搜索算法优点的混和优化策略，该策略针对配电网检修计划优化问题的特点设计了3种疫苗，并且构造了2阶段变异，在优化前期使用禁忌搜索变异算子，而在优化后期恢复为一般变异算子，从而保证了算法的快速收敛。通过实际计算和分析，验证了文中所提出模型和算法的正确性和实用性，以及与遗传禁忌混合智能算法相比的优越性，实例计算结果表明本文所采用的方法是有效的，免疫禁忌混合智能算法在收敛速度，爬山能力，解的质量和稳定性上都要优于遗传禁忌组合算法，更适合求解配电网检修优化问题。

DISTRIBUTION MAINTENANCE SCHEDULING USING AN INTELLIGENT OPTIMAL APPROACH MIXED WITH IMMUNE ALGORITHM AND TABU SEARCH

A new model for distribution maintenance scheduling which intends to find the most economical maintenance schedule without violating any restrictions is proposed in this paper. To solve this complicate problem,this paper presents a hybrid strategy that sufficiently combines the advantages of Immune Algorithm(IA) and Tabu Search(TS). By constructing three effective bacterins which derive from the features of distribution maintenance schedule and introducing TS into mutation operation of IA in the earlier generations,the hybrid strategy improves the convergence of optimization and shortens the calculation time. The proposed model and method are applied to a practical system, and numerical results verify the correctness and validity of them.