Robust multiobjective optimization with application to Internet routing
Robust multiobjective optimization with application to Internet routing
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DOI：
10.1007/s10479-017-2751-5
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发表时间：
2018-02
影响因子：
4.8
通讯作者：
Erin K. Doolittle;H. Kerivin;M. Wiecek
中科院分区：
文献类型：
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作者：
Erin K. Doolittle;H. Kerivin;M. Wiecek
鲁棒优化解决不确定性下的决策问题已经非常好地发展为具有单一目标函数的问题，并应用于人类活动的领域，如投资组合选择，投资决策，信号处理，以及网络规划。由于这些决策问题通常有几个决定或目标，我们扩展了强大的单目标优化的多目标的情况下。列的不确定性模型可以结转到多目标的情况下，没有任何额外的假设。对于行的不确定性模型，我们表明，在额外的假设下，强大的有效的解决方案是有效的具体实例问题，可以找到另一个确定性问题的有效解决方案。互联网流量必须保持在一个可靠的，但负担得起的方式在复杂的和动态的使用情况下的事实的动机，我们应用行明智的模型，一个域内多目标路由问题与多面体流量的不确定性。我们认为传统的目标函数对应的链路利用率和实现的双目标的情况下，使用参数单纯形算法计算强大的有效路由。我们还提出了Abilene网络的计算结果，并分析其意义的上下文中的应用。
Robust optimization addressing decision making under uncertainty has been very well developed for problems with a single objective function and applied to areas of human activity such as portfolio selection, investment decisions, signal processing, and telecommunication-network planning. As these decision problems typically have several decisions or goals, we extend robust single objective optimization to the multiobjective case. The column-wise uncertainty model can be carried over to the multiobjective case without any additional assumptions. For the row-wise uncertainty model, we show under additional assumptions that robust efficient solutions are efficient to specific instance problems and can be found as the efficient solutions of another deterministic problem. Being motivated by the fact that Internet traffic must be maintained in a reliable yet affordable manner in situations of complex and dynamic usage, we apply the row-wise model to an intradomain multiobjective routing problem with polyhedral traffic uncertainty. We consider traditional objective functions corresponding to link utilizations and implement the biobjective case using the parametric simplex algorithm to compute robust efficient routings. We also present computational results for the Abilene network and analyze their meaning in the context of the application.