Abstract
In large-scale computer communication networks (e.g. the nowadays Internet), the assignment of link capacity and the selection of routes (or the assignment of flows) are extremely complex network optimization problems. Efficient solutions to these problems are much sought after because such solutions could lead to considerable monetary savings and better utilization of the networks. Unfortunately, as indicated by much prior theoretical research, these problems belong to the class of nonlinear combinatorial optimization problems, which are mostly (if not all) NP-hard problems. Although the traditional Lagrange relaxation and sub-gradient optimization methods can be used for tackling these problems, the results generated by these algorithms are locally optimal instead of globally optimal. In this paper, we propose a genetic algorithm based approach to providing optimized integrated solutions to the route selection and capacity flow assignment problems. With our novel formulation and genetic modeling, the proposed algorithm generates much better solutions than two well known efficient methods in our simulation studies.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.