首页> 外文期刊>IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics >Evolutionary Algorithms Refining a Heuristic: A Hybrid Method for Shared-Path Protections in WDM Networks Under SRLG Constraints
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Evolutionary Algorithms Refining a Heuristic: A Hybrid Method for Shared-Path Protections in WDM Networks Under SRLG Constraints

机译:改进启发式算法的进化算法:在SRLG约束下WDM网络中共享路径保护的混合方法

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An evolutionary algorithm (EA) can be used to tune the control parameters of a construction heuristic to an optimization problem and generate a nearly optimal solution. This approach is in the spirit of indirect encoding EAs. Its performance relies on both the heuristic and the EA. This paper proposes a three-phase parameterized construction heuristic for the shared-path protection problem in wavelength division multiplexing networks with shared-risk link group constraints and applies an EA for optimizing the control parameters of the proposed heuristics. The experimental results show that the proposed approach is effective on all the tested network instances. It was also demonstrated that an EA with guided mutation performs better than a conventional genetic algorithm for tuning the control parameters, which indicates that a combination of global statistical information extracted from the previous search and location information of the best solutions found so far could improve the performance of an algorithm
机译:进化算法(EA)可用于调整构造启发式算法的控制参数以优化问题,并生成接近最优的解决方案。这种方法本着间接编码EA的精神。它的性能取决于启发式方法和EA。针对具有共享风险链路组约束的波分复用网络中的共享路径保护问题,本文提出了一种三相参数化构造启发式算法,并应用了EA来优化该启发式算法的控制参数。实验结果表明,该方法在所有测试的网络实例上均有效。还证明了带有指导突变的EA的性能优于传统的遗传算法来调节控制参数,这表明从先前的搜索中提取的全局统计信息与迄今为止找到的最佳解决方案的位置信息的组合可以改善算法的性能

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