Skip to Main Content
Restoration techniques available in the literature have not addressed their performance in terms of significant, multiple objective goals. Some of these methods have shown good performance for a single objective function. However, restoration must consider a number of objective functions. We evaluate existing models and their performance in an attempt to verify their performance and efficacy based on the literature. Our research has found not only inefficiency in some of these methods of restoration, but a general incompatibility. Consequently, This work proposes eight objective functions that yield objective goals significant to the optimal design of a WDM (wavelength division multiplexing) optical network. Each objective function model is presented and is examined by experimentation. Four proposed restoration algorithms are evaluated: KSDPR (k-shortest disjoint path restoration based on multiple uphill moves and heuristic rule), DCROS (deep conjectural reinforced optimal search), RWWA (random walk-based wavelength assignment), and PTCI (physical topology connectivity increase). Numerical results obtained by experimental evaluation of KSDPR, DCROS, RWWA, and PTCI algorithms confirm that MTWM (objective function of minimizing total wavelengths with multi-objective goals) based on the DCROS algorithm is a technique for efficient restoration in WDM optical networks.