On Improving the Capacity of Solving Large-scale Wireless Network Design Problems by Genetic Algorithms

Abstract

Abstract. Over the last decade, wireless networks have experienced an impressive growth and now play a main role in many telecommunications systems. As a consequence, scarce radio resources, such as frequencies, became congested and the need for effective and efficient assignment methods arose. In this work, we present a Genetic Algorithm for solving large instances of the Power, Frequency and Modulation Assignment Problem, arising in the design of wireless networks. To our best knowledge, this is the first Genetic Algorithm that is proposed for such problem. Compared to previous works, our approach allows a wider exploration of the set of power solutions, while eliminating sources of numerical problems. The performance of the algorithm is assessed by tests over a set of large realistic instances of a Fixed WiMAX Network.

A Fast ILP-Based Heuristic for the Robust Design of Body Wireless Sensor Networks

“…As future work, we plan to further reduce the optimality gap by considering other integration of heuristics (in particular, genetic and sequential heuristics like in [31,32]) and cutting plane methods identifying conflicts between variables, as in [33,34]. Also, we intend to evaluate biobjective versions of the problem, considering the trade-off between relay deployment cost and energy consumption and adopting an algorithm similar to [35].…”

An (MI)LP-Based Primal Heuristic for 3-Architecture Connected Facility Location in Urban Access Network Design

“…In principle, all these parameters can be set in an optimal way, by expressing their setting through a suitable mathematical optimization problem. However, just a (small) subset of parameters are typically optimized in a wireless network design problem [6,14]. A decision that is included in practically every design problem is the setting of power emissions.…”

“…to the procedure using the probability measures (14) and update formulas (15) that we have discussed before. The complete FOS provides a (partial) fixing of the facility opening variablesz and the MIP solver uses it as a basis for finding a complete feasible solution X * to the problem.…”

A Hybrid Exact-ACO Algorithm for the Joint Scheduling, Power and Cluster Assignment in Cooperative Wireless Networks

“…The constraints (7) ensure that each BS emits at a single power level, while the constraints (8)-(10) operate the linearization of the product z bl y tb . Finally, (11)- (14) define the decision variables of the problem.…”

“…The main objective of our work is to make further steps towards closing such gap. Specifically, our original contributions are: 1) a new binary linear model for the design of cooperative wireless networks, that jointly optimizes activated service links, power emissions and cooperative clusters; 2) a strengthening procedure that generates a stronger optimization model, in which sources of numerical issues are completely eliminated; 3) a hybrid solution algorithm, based on the combination of a special exact large neighborhood search called RINS [11] with ant colony optimization [20] (note that tough generic heuristics and pure and hybrid nature-inspired metaheuristics are not a novelty in (wireless) network design -see e.g., [3,5,9,14] -to the best of our knowledge such combination has not yet been investigated). This algorithm is built to effectively exploit the precious information coming from the stronger model and can rapidly find solutions of very satisfying quality.…”