Assigning cells to switches in cellular mobile networks using taboo search

Abstract

The design of wireless telecommunications networks is a complex process, which requires solving simultaneously many difficult combinatorial optimization problems. We propose a taboo-search approach dedicated to one of the aforementioned design optimization problems, namely the cell assignment problem. Our approach defines a series of moves applicable to an initial solution in order to improve the cost and establish the feasibility of the solution. For this purpose, we identify a gain structure with update procedures to efficiently choose the best solution in the current neighborhood. The results are generally good in comparison with those obtained through other heuristic methods.

Assignment of cells to switches in a cellular mobile network using a hybrid Hopfield network-genetic algorithm approach

“…The values of l i , M k and the positions of the cells and switches for this problem are given in Tables 3 and 4. Note that the trend is to assign as many cells as possible 3 to the nearest switch (switch 2 in this case). Cells in the center of the network, which have more probability of handoff than other cells, are always assigned to the same switch.…”

“…In [3], Pierre and Houéto discussed an approach based on TS. In this paper the authors showed that their TS approach outperforms a simulated annealing (SA) approach for the CTSAP.…”

“…1 for example) it is called simple handoff. This type of handoff is relatively easy to perform, and does not involve any location update in the databases that record the position of the user [1,3]. Imagine now that a user moves from cell B to cell C. In this case, the process of handoff involves the execution of a complicated protocol between switches 1 and 2 (see Fig.…”

“…These papers present some heuristic algorithms to solve the problem. Several other heuristics techniques have been applied to the CTSAP, such as tabu search [3,5], simulated annealing [2], genetic algorithms [6] and hybrid algorithms which mix genetic algorithms and local search heuristics [7,8].…”

Task mapping and priority assignment for soft real-time applications under deadline miss ratio constraints

“…It has been successfully used for various system-level design problems, such as yield maximization problems [Alippi et al 2003], FIR filter design [Traferro et al 1999], mapping and scheduling of task graphs on SoCs [Wild et al 2003], and latency-area tradeoffs for NoCs [Cardoso et al 2005]. Several researchers have compared tabu search with other optimization heuristics, such as simulated annealing and genetic algorithms and shown the superiority of tabu search with regard to optimization time and quality of results [Hajji et al 2002;Wild et al 2003;Pierre and Houeto 2002;Krishnamachari and Wicker 2000;Eles et al 1997].…”