A novel grouping harmony search algorithm for the multiple-type access node location problem

In this paper we present a novel grouping harmony search algorithm for the Access Node Location Problem (ANLP) with different types of concentrators. The ANLP is a NP-hard problem where a set of distributed terminals, with distinct rate demands, must be assigned to a variable number of concentrators subject to capacity constraints. We consider the possibility of choosing between different concentrator models is given in order to provide service demand at different cost. The ANLP is relevant in communication networks design, and has been considered before within the design of MPLS networks, for example. The approach we propose to tackle the ANLP problem consists of a hybrid Grouping Harmony Search (GHS) algorithm with a local search method and a technique for repairing unfeasible solutions. Moreover, the presented scheme also includes the adaptation of the GHS to a differential scheme, where each proposed harmony is obtained from the same harmony in the previous iteration. This differential scheme is perfectly adapted to the specifications of the ANLP problem, as it utilizes the grouping concept based on the proximity between nodes, instead of being only based on the grouping concept. This allows for a higher efficiency on the searching process of the algorithm. Extensive Monte Carlo simulations in synthetic instances show that this proposal provides faster convergence rate, less computational complexity and better statistical performance than alternative algorithms for the ANLP, such as grouping genetic algorithms, specially when the size of the scenario increases. We also include practical results for the application of GHS to a real wireless network deployment problem in Bizkaia, northern Spain.

[1]  Roger L. Wainwright,et al.  Terminal assignment in a communications network using genetic algorithms , 1994, CSC '94.

[2]  Stephen B. Wicker,et al.  Base Station Location Optimization in Cellular Wireless Networks using Heuristic Search Algorithms , 2004 .

[3]  Kumbesan Sandrasegaran Planning point-to-multipoint rural radio access networks using expert systems , 1999 .

[4]  Z. Geem Optimal Design of Water Distribution Networks Using Harmony Search , 2009 .

[5]  El-Sayed M. El-Alfy Applications of genetic algorithms to optimal multilevel design of MPLS-based networks , 2007, Comput. Commun..

[6]  Zong Woo Geem,et al.  A New Heuristic Optimization Algorithm: Harmony Search , 2001, Simul..

[7]  Javier Del Ser,et al.  A novel heuristic algorithm for multiuser detection in synchronous CDMA wireless sensor networks , 2009, 2009 International Conference on Ultra Modern Telecommunications & Workshops.

[8]  Emanuel Falkenauer,et al.  A New Representation and Operators for Genetic Algorithms Applied to Grouping Problems , 1994, Evolutionary Computation.

[9]  Tabitha L. James,et al.  A hybrid grouping genetic algorithm for the registration area planning problem , 2007, Comput. Commun..

[10]  Alok Singh,et al.  A new grouping genetic algorithm approach to the multiple traveling salesperson problem , 2008, Soft Comput..

[11]  Javier Del Ser,et al.  A novel Harmony Search based spectrum allocation technique for cognitive radio networks , 2010, 2010 7th International Symposium on Wireless Communication Systems.

[12]  Xin Yao,et al.  Optimal switch location in mobile communication networks using hybrid genetic algorithms , 2008, Appl. Soft Comput..

[13]  Sancho Salcedo-Sanz,et al.  A hybrid grouping genetic algorithm for assigning students to preferred laboratory groups , 2009, Expert Syst. Appl..

[14]  Xin Yao,et al.  A hybrid Hopfield network-genetic algorithm approach for the terminal assignment problem , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[15]  Abolfazl Toroghi Haghighat,et al.  Harmony search based algorithms for bandwidth-delay-constrained least-cost multicast routing , 2008, Comput. Commun..

[16]  Javier Del Ser,et al.  Harmony Search Heuristics for Quasi-asynchronous CDMA Detection with M-PAM Signalling , 2010, MOBILIGHT.

[17]  Evelyn C. Brown,et al.  A grouping genetic algorithm for the microcell sectorization problem , 2004, Eng. Appl. Artif. Intell..

[18]  Ming-Shi Wang,et al.  Broadcast scheduling in wireless sensor networks using fuzzy Hopfield neural network , 2008, Expert Syst. Appl..

[19]  S. Menon,et al.  Assigning cells to switches in cellular networks by incorporating a pricing mechanism into Simulated annealing , 2004, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).