Hyper-heuristic genetic algorithm for solving frequency assignment problem in TD-SCDMA

This paper studies the frequency assignment problem (FAP) in TD-SCDMA network of mobile communications industry in China. The problem considers finding the optimal frequency allocation scheme for carriers with a limited frequency resource, such that the entire network interference is minimized. Besides, the allocation of frequencies needs to satisfy some constraints to avoid the effect of call interference within the same cell or adjacent cell. Given the formula for calculation of the network interference, we take the FAP as a constrained optimization problem and use a hyper-heuristic genetic algorithm (HHGA) to optimize the assignment of frequencies. We first define six low-level heuristics (LLHs) search strategies based on the computation of interference, and then use genetic algorithm (GA) at a high-level to find the best combination sequence of LLH strategies to reduce interferences of the overall network. GA uses two-point crossover, uniform mutation, and Minimal Generation Gap (MGG) as the generation alternation model. In order to speed up the search, we define a Tabu table to avoid repeat search of LLHs. Compared with scatter search as one of the meta-heuristic algorithm with best performance, our experimental results on real data sets of TD-SCDMA network have shown better result.

[1]  Jin-Kao Hao,et al.  Tabu Search for Frequency Assignment in Mobile Radio Networks , 1998, J. Heuristics.

[2]  W. K. Hale.  Frequency assignment: Theory and applications , 1980, Proceedings of the IEEE.

[3]  Sanja Petrovic,et al.  Case-based heuristic selection for timetabling problems , 2006, J. Sched..

[4]  Matteo Fischetti,et al.  Frequency assignment in mobile radio systems using branch-and-cut techniques , 2000, Eur. J. Oper. Res..

[5]  Graham Kendall,et al.  A Classification of Hyper-heuristic Approaches , 2010 .

[6]  Carlo Mannino,et al.  An Enumerative Algorithm for the Frequency Assignment Problem , 2003, Discret. Appl. Math..

[7]  Enrique Alba,et al.  ACO vs EAs for solving a real-world frequency assignment problem in GSM networks , 2007, GECCO '07.

[8]  Shigenobu Kobayashi,et al.  A robust real-coded genetic algorithm using Unimodal Normal Distribution Crossover augmented by Uniform Crossover: effects of self-adaptation of crossover probabilities , 1999 .

[9]  Graham Kendall,et al.  Channel assignment in cellular communication using a great deluge hyper-heuristic , 2004, Proceedings. 2004 12th IEEE International Conference on Networks (ICON 2004) (IEEE Cat. No.04EX955).

[10]  Graham Kendall,et al.  An investigation of a tabu assisted hyper-heuristic genetic algorithm , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[11]  Ruibin Bai,et al.  An investigation of novel approaches for optimising retail shelf space allocation , 2005 .

[12]  Ken-ichi Tokoro,et al.  An Efficient Hybrid Genetic Algorithm for a Fixed Channel Assignment Problem with Limited Bandwidth , 2003, GECCO.

[13]  G. Kendall,et al.  Channel assignment optimisation using a hyper-heuristic , 2004, IEEE Conference on Cybernetics and Intelligent Systems, 2004..

[14]  Edmund K. Burke,et al.  A hybrid heuristic ordering and variable neighbourhood search for the nurse rostering problem , 2004, Eur. J. Oper. Res..

[15]  Enrique Alba,et al.  Optimization algorithms for large-scale real-world instances of the frequency assignment problem , 2010, Soft Comput..

[16]  Guo Yong-ming.  Discussion on TD-SCDMA Network Interference , 2010 .

[17]  Carlo Mannino,et al.  Models and solution techniques for frequency assignment problems , 2003, 4OR.