A GRASP with path-relinking heuristic for the survivable IP/MPLS-over-WSON multi-layer network optimization problem

Authors:
Oscar Pedrola;Marc Ruiz;Luis Velasco;Davide Careglio;Oscar González De Dios;Jaume Comellas
Affiliations:
Advanced Broadband Communications Center (CCABA), Universitat Politècnica de Catalunya (UPC), 08034 Barcelona, Spain;Advanced Broadband Communications Center (CCABA), Universitat Politècnica de Catalunya (UPC), 08034 Barcelona, Spain;Advanced Broadband Communications Center (CCABA), Universitat Politècnica de Catalunya (UPC), 08034 Barcelona, Spain;Advanced Broadband Communications Center (CCABA), Universitat Politècnica de Catalunya (UPC), 08034 Barcelona, Spain;Telefónica I+D, Don Ramón de la Cruz 82-84, 28006 Madrid, Spain;Advanced Broadband Communications Center (CCABA), Universitat Politècnica de Catalunya (UPC), 08034 Barcelona, Spain
Venue:
Computers and Operations Research
Year:
2013

Citing 17
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Abstract

In this paper we deal with the survivable internet protocol (IP)/multi-protocol label switching (MPLS)-over-wavelength switched optical network (WSON) multi-layer network optimization problem (SIMNO). This problem entails planning an IP/MPLS network layer over a photonic mesh infrastructure whilst, at the same time, ensuring the highest availability of services and minimizing the capital expenditures (CAPEX) investments. Such a problem is currently identified as an open issue among network operators, and hence, its solution is of great interest. To tackle SIMNO, we first provide an integer linear programming (ILP) formulation which provides an insight into the complexity of its managing. Then, a greedy randomized adaptive search procedure (GRASP) with path-relinking (PR) together with a biased random-key genetic algorithm (BRKGA) are specifically developed to help solve the problem. The performance of both heuristics is exhaustively tested and compared making use of various network and traffic instances. Numerical experiments show the benefits of using GRASP instead of BRKGA when dealing with highly complex network scenarios. Moreover, we verified that the use of GRASP with PR remarkably improves the basic GRASP algorithm, particularly in real-sized, complex scenarios such as those proposed in this paper.