Title :
Optimising the deployment of fibre optics using Guided Local Search
Author :
Cramer, Sam ; Kampouridis, Michael
Author_Institution :
University of Kent
Abstract :
The deployment of fibre optics poses a huge investment risk, thus telecommunication companies are skeptical about replacing copper given the high cost of doing so. Over recent times, the usage of the internet has changed and led to a need for fibre optics. The decision on whether to deploy or not is made through the use of complex models. However, the problem being that deployment plans are manually predefined based on previous knowledge, this process does not guarantee that the plans are optimal. This paper demonstrates that the deployment of fibre optics can be optimised by using intelligent algorithms. We implemented a metaheuristic (Guided Local Search) to the problem to demonstrate the effectiveness and benefit of looking for an optimal deployment plan. Results indicate that Guided Local Search lead to a significant increase in the profit and can address the problem of finding an optimal deployment plan.
Keywords :
Biological system modeling; Cities and towns; Communications technology; Companies; Economics; Optics; Search problems;
Conference_Titel :
Evolutionary Computation (CEC), 2015 IEEE Congress on
Conference_Location :
Sendai, Japan
DOI :
10.1109/CEC.2015.7256973