ABSTRACT Nowadays, nature-inspired metaheuristic algorithms are the most powerful optimizing algorithms for solving NP-complete problems. This paper proposes five recent approaches to find near-optimal Golomb ruler (OGR) sequences based on nature-inspired algorithms in a reasonable time. The optimal Golomb ruler sequences found their application in channel-allocation method that allows suppression of the crosstalk due to four-wave mixing (FWM) in optical wavelength division multiplexing (WDM) systems. The simulation results conclude that the proposed nature-inspired metaheuristic optimization algorithms are superior to the existing conventional computing algorithms, i.e., Extended Quadratic Congruence (EQC) and Search algorithm (SA) and nature-inspired algorithms, i.e., Genetic algorithms (GAs), Biogeography-based optimization (BBO) and simple Big bang–Big crunch (BB-BC) optimization algorithm to find near-OGRs in terms of ruler length, total optical channel bandwidth and computation time.

中文翻译：

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自然启发式元启发式算法的比较研究，为 WDM 系统中的 FWM 串扰消除寻找接近最优的 Golomb 标尺

摘要 如今，受自然启发的元启发式算法是解决 NP 完全问题的最强大的优化算法。本文提出了五种最近的方法，以在合理的时间内基于自然启发的算法找到接近最优的哥伦布标尺 (OGR) 序列。最佳哥伦布标尺序列在信道分配方法中得到了应用，该方法允许抑制由于光波分复用 (WDM) 系统中的四波混合 (FWM) 引起的串扰。仿真结果表明，所提出的自然启发式元启发式优化算法优于现有的常规计算算法，即扩展二次同余（EQC）和搜索算法（SA）和自然启发算法，即遗传算法（GAs），