An improved tabu search algorithm for the fixed-spectrum frequency-assignment problem

Montemanni, Roberto; Moon, Jim; Smith, Derek H.

doi:10.1109/tvt.2003.810976

Cited by 64 publications

(65 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Test problems are six artificial instances. Montemanni et al (2003) also consider the distance MS-FAP with the default neighborhood, but with a dynamic tabu list, i.e., the length of the list reduces with every iteration similar to the temperature parameter of simulated annealing, cf. Sect.…”

Section: Mi-fap Inmentioning

confidence: 99%

Models and solution techniques for frequency assignment problems

et al. 2007

View full text Add to dashboard Cite

Wireless communication is used in many different situations such as mobile telephony, radio and TV broadcasting, satellite communication, wireless LANs, and military operations. In each of these situations a frequency assignment problem arises with application specific characteristics. Researchers have developed different modeling ideas for each of the features of the problem, such as the handling of interference among radio signals, the availability of frequencies, and the optimization criterion.This survey gives an overview of the models and methods that the literature provides on the topic. We present a broad description of the practical settings in which frequency assignment is applied. We also present a classification of the different models and formulations described in the literature, such that the common features of the models are emphasized. The solution methods are divided in two parts. Optimization and lower bounding techniques on the one hand, and heuristic search techniques on the other hand. The literature is classified according to the used methods. Again, we emphasize the common features, used in the different papers. The quality of the solution methods is compared, whenever possible, on publicly available benchmark instances. This is an updated version of a paper that appeared in 4OR 1, 261-317, 2003.

show abstract

Section: Mi-fap Inmentioning

confidence: 99%

Models and solution techniques for frequency assignment problems

et al. 2007

View full text Add to dashboard Cite

show abstract

“…This indicates that if the practitioners evolve towards real time computations and decisions, T abuApproxObj is the most appropriate algorithm among the ones presented here. Note that on these instances, T abuLevel is not competitive with the two other tabu search algorithms, which means that straightforward adaptation of efficient algorithms in GSM networks (see [11,16]) to WLAN networks are not appropriate. However, we feel that it may be appropriate for networks with very large value of n · d and for real time computation (i.e.…”

Section: Numerical Results and Conclusionmentioning

confidence: 99%

Three tabu search methods for the MI-FAP applied to 802.11 networks

Varone¹,

Zufferey

2008

RAIRO-Oper. Res.

View full text Add to dashboard Cite

Abstract. Wireless LAN using IEEE 802.11 networks are now widely deployed at home by residential users or in hot spots by telecommunication operators. A hot spot is a place where a set of access points (APs) are located nearby each other and can serve many users. Since perturbations can degrade the quality of the signal, a careful channel assignment to each AP has to be done. Channel assignment of APs at hot spots, and more generally setup configuration and management, is still often done manually. In this paper, we consider a modeling that enables optimization of channel assignment with respect to the dynamic behavior of end-users. We prove our problem's formulation to correspond to the Minimum Interference Frequency Assignment Problem, and hence the problem to be NP-hard. We propose and compare three different tabu search methods to solve the problem of channel assignment in 802.11 WLAN networks. The first one, called T abuObj, tackles the problem using directly the objective function associated with the model. The second one, called T abuApproxObj, uses a simplified and approximate objective function in order to visit more solutions during the same amount of time, i.e. to be quicker than T abuObj. The third one, called T abuLevel, is even more quicker and is based on the following philosophy: under time constraints, it could be judicious to explore very quickly lots of solutions, rather than spending much computation time for the evaluation of each solution, and hence only considering a few solutions. Those three methods are then compared based on time constraints and on the quality of their solutions.

show abstract

“…The TS procedure adopts the conflict-based neighborhood Hao et al, 1998;Montemanni et al, 2003). Given a solution s, a neighboring solution of s with respect to this neighborhood is obtained by changing the value (frequency) of one conflicting variable (vertex) u from its original frequency f i to another frequency f j (denoted by < u, f i , f j >), and the resulting neighborhood N (s) is composed of all such neighboring solutions.…”

Section: Neighborhood Structurementioning

confidence: 99%

“…Given the high complexity of FS-FAP, considerable efforts have been made to develop effective heuristic methods. These include single solution based approaches like tabu search (Castelino et al, 1996;Hao et al, 1998;Montemanni et al, 2003), adaptive local search (Kendall and Mohamad, 2004), heuristic manipulation technique (Montemanni and Smith, 2010). Populationbased approaches are also very popular: ANTS algorithm (Maniezzo and Carbonaro, 2000), genetic algorithms (Dorne and Hao, 1996;Park et al, 2002;San Jose-Revuelta, 2007), hybrid evolutionary algorithms (Dorne and Hao, 1995;Jin et al, 2001;Kim et al, 2007;Lai and Coghill, 1996), multiple strategy method (Hurley et al, 1997).…”

Section: Introductionmentioning

confidence: 99%

Path relinking for the fixed spectrum frequency assignment problem

Lai

Hao

2015

Expert Systems with Applications

View full text Add to dashboard Cite

The fixed spectrum frequency assignment problem (FS-FAP) is a highly relevant application in modern wireless systems. This paper presents the first path relinking (PR) approach for solving FS-FAP. We devise four relinking operators to generate intermediate solutions (or paths) and a tabu search procedure for local optimization. We also adopt a diversity-and-quality technique to maintain population diversity. To show the effectiveness of the proposed approach, we present computational results on the set of 42 benchmark instances commonly used in the literature and compare them with the current best results obtained by any other existing methods. By showing improved best results (new upper bounds) for 19 instances, we demonstrate the effectiveness of the proposed PR approach. We investigate the impact of the relinking operators and the population updating strategy. The ideas of the proposed could be applicable to other frequency assignment problems and search problems.

show abstract

An improved tabu search algorithm for the fixed-spectrum frequency-assignment problem

Cited by 64 publications

References 19 publications

Models and solution techniques for frequency assignment problems

Models and solution techniques for frequency assignment problems

Three tabu search methods for the MI-FAP applied to 802.11 networks

Path relinking for the fixed spectrum frequency assignment problem

Contact Info

Product

Resources

About