Variable neighborhood search approach with intensified shake for monitor placement

Abstract

Several problems are emerging in the context of communication networks and most of them must be solved in reduced computing time since they affect to critical tasks. In this research, the monitor placement problem is tackled. This problem tries to cover the communications of an entire network by locating a monitor in specific nodes of the network, in such a way that every link remains surveyed. In case that a solution cannot be generated in the allowed computing time, a penalty will be assumed for each link uncovered. The problem is addressed by considering the variable neighborhood search framework, proposing a novel constructive method, an intelligent local search to optimize the improvement phase, and an intensified shake to guide the search to more promising solutions. The proposed algorithm is compared with a hybrid search evolutionary algorithm over a set of instances derived from real-life networks to prove its performance.

The multiobjective traveling salesman–repairman problem with profits: design and implementation of a variable neighborhood descent algorithm for a real scenario

“…Having defined the proposed VND, it is necessary to describe how to generate the initial approximation of the Pareto front, P F , since this will be one of the inputs of VND. The original hypothesis of VNS methodology (Hansen and Mladenović, 2001) suggests that considering random initial solutions does not affect to the performance of the algorithm, but it has been recently shown that VNS performs better (in the context of multiobjective optimization, we consider that a solution is better than another one if the new solution dominates the original one) when starting from promising regions of the search space, such as for the monitor placement problem (Casado et al, 2022a) and for the multiobjective community detection problem (Pérez-Peló et al, 2021). In this work, we propose a constructive method based on the constructive part of GRASP, which includes a diversification phase, namely GRA construction, useful in a multiobjective context such as this research (Feo et al, 1994;Feo and Resende, 1995).…”