Orateur
Description
We consider the wavelength dimensioning problem in wavelength division multiplexing optical networks, which aims to determine the set of wavelengths assigned to each link to accommodate future connection requests under uncertain traffic conditions. To tackle this, we propose a two-stage chance-constrained mixed-integer programming (2S-CCMIP) model that minimizes the total assigned wavelength capacity while ensuring (in the second stage, via a proper routing and wavelength assignment model) operational performance requirements are met with high probability, based on a given risk tolerance. To achieve reductions in the allocated wavelength capacity while accommodating heterogeneous traffic densities across the network, we use a non-uniform dimensioning strategy that allows different links to have different set of assigned wavelengths. For solving the 2S-CCMIP model, we develop a tailored branch-and-cut algorithm, incorporating problem-specific cutting planes. We also design a novel heuristic method that generates feasible solutions from any infeasible integer solution. We propose a two-phase framework that effectively integrates the proposed enhancements. Through numerical experiments on three real-world network topologies, we demonstrate the effectiveness of our method in reducing wavelength capacity and improving computational efficiency compared to existing alternatives.
