This non-conventional paper represents the first attempt to uncover a possible vulnerability in some proposals for optical network designs and performance comparisons. While optical network designs and planning lie at the heart of achieving fiber capacity efficiency and/or operational efficiency, its combinatorial nature makes it computationally hard to reach optimal solutions for realistic scenarios. Therefore, the well-established way that have been taken for granted by not-so-small number of research papers is that an optimization model based on mixed integer linear programming (MILP) is first proposed and then due to the intractability of such combinatorial model, an heuristic algorithm is offered as an approximation. The solution-quality comparison between the MILP and heuristic is then carried out on small-scale instances including topologies and traffic tests to verify the efficacy of the proposed heuristic and the next step is to use such allegedly verified heuristic for optical network designs of realistic scenarios. This approach may nevertheless leave a critical vulnerability as there is no guarantee that one performs well in small tests will generalize adequately for large-scale cases, a common pitfall widely referred as the peril of extrapolation and/or overfitting. Besides, it is not uncommon that in some research works, for benchmarking purpose, the comparison between a new design proposal whose performance is obtained from on one heuristic and a reference design based on another heuristic is carried out. As the result of missing solution quality check, such performance comparison relied merely on heuristic solutions may be equally vulnerable as its results can be distorted and thus, be far from the possibly achieved zones. In this work, we pinpoint those issues and provide a realistic case study to highlight and demonstrate the impact of such vulnerabilities.
翻译:虽然光学网络设计和规划是实现纤维能力效率和(或)操作效率的核心,但其组合性质使得很难计算出为现实情景找到最佳解决办法。因此,非如此之少的研究论文所认定的既定方法是,首先提出基于混合整数线性编程的优化模式,然后由于这种组合式模型的易碎性,因此提出超常性算法作为近似值。虽然光学网络设计和规划是实现纤维能力效率和(或)操作效率的核心,但其组合性性质使得它很难在计算实际情景时找到最佳解决办法。因此,基于不那么少的研究论文的既定方法认为,基于混合整数线性编程的优化模型(MILP)的优化模式首先被提出,然后由于这种组合性模型的易碎度模型的易碎度模型的易碎化性,一种超常的算法被广泛称为超常性推论和(或)超常性能比较。 此外,在设计性能设计过程中,可能存在一种非常罕见的情况是,在设计上,在设计结果上,在设计结果上,在设计结果上,一种非常罕见的结果是,在设计上是,在设计上,在一种非常罕见的结果是,在设计上是,在设计上,在设计上,在设计上,在一种非常罕见的,在设计上是,在设计上,在设计上是,在设计上,在设计上是,在设计上,在设计上,在进行一种非常不寻常性研究上,在一种结果上,从一种不同的结果,在一种比较。在一种结果上,在一种不同的结果是,在进行,在一种不同的结果是,在一种比较,在一种比较,在一种不同,在一种不同的结果,在一种比较,在一种比较,在一种不同,在一种比较是,在一种是,在一种比较。在一种比较,在一种比较,在一种比较,在一种比较。在一种比较,在一种,在一种比较,在一种比较,在一种比较,在一种比较,在一种比较,在一种比较,在一种比较是,在一种比较是,在一种比较,在一种不同,在一种,在一种情况下,在一种情况下,在一种情况下,在一种情况下,在一种情况下,在一种情况下,在一种情况下,在一种情况下,在一种,在一种比较,在一种,在一种,在一种