A memetic algorithm for channel assignment in wireless FDMA systems

Kim, Sung‐Soo; Smith, Alice E.; Lee, Jong‐Hyun

doi:10.1016/j.cor.2005.05.038

Cited by 20 publications

(14 citation statements)

References 18 publications

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“…In order for a GA to perform well on AFP problems, its hybridization with a local search algorithm is almost mandatory. Indeed, the most recent and efficient GAs for solving several flavors of the problem are endowed with some kind of local search: a probabilistic Tabu Search in (Alabau et al 2002), an adaptation of Markov Decision Processes in (Idoumghar and Schott 2006), the CAP3 method in (Kim, Smith and Lee 2007), or others specifically designed for the problem being solved (Colombo 2006, Matsui, Watanabe andTokoro 2003). The usage of local search turned out also to be essential in ACO algorithms for solving frequency assignment problems (Graham, Montemani, Moon and Smith 2007), and particularly in the version of the AFP problem used, as shown in (Luna et al 2007).…”

Section: Solution Encoding and Genetic Operatorsmentioning

confidence: 99%

Solving large-scale real-world telecommunication problems using a grid-based genetic algorithm

Luna¹,

Nebro²,

Alba³

et al. 2008

Engineering Optimization

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. Solving large-scale real-world telecommunication problems using a grid-based genetic algorithm. Engineering Optimization, Taylor Francis, 2008, 40 (11) AbstractThis paper analyzes the use of a grid-based genetic algorithm (GrEA) to solve a real-world instance of a problem from the telecommunication domain. The problem, known as automatic frequency planning (AFP), is used in GSM networks (Global System for Mobile communications) to assign a number of fixed frequencies to a set of GSM transceivers located in the antennae of a cellular phone network. Real data instances of the AFP are very difficult to solve due to the NP-hard nature of the problem, so combining grid computing and metaheuristics comes out as a way to provide satisfactory solutions in a reasonable amount of time. GrEA has been deployed on a grid with up to 300 processors to solve an AFP instance of 2,612 transceivers. The results not only show that significant running times reductions are achieved, but that the search capability of GrEA outperforms clearly that of the equivalent non-grid algorithm.

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Section: Solution Encoding and Genetic Operatorsmentioning

confidence: 99%

Solving large-scale real-world telecommunication problems using a grid-based genetic algorithm

Luna¹,

Nebro²,

Alba³

et al. 2008

Engineering Optimization

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“…It depends with the availability of channels in certain time periods. The approaches can be divided into three conditions which are static, dynamic and flexible allocation [5]. In static allocation, past patterns of demand are analyzed where based on the obtained information, the requirement of channels is predicted.…”

Section: IImentioning

confidence: 99%

A permutation based technique for channel assignment problem

Suliman

Kendall

Musirin

et al. 2010

2010 IEEE Student Conference on Research and Development (SCOReD)

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Channel assignment problem is an example of NP complete problem in which the complexity and level of difficulty depends on the input parameters of a particular condition.Therefore, a good technique with an efficient optimization approach will produce a good assignment if not optimum. This paper proposes the use of permutation technique adopted from evolutionary strategy in producing various number of cell orders for channel assignment task. Subject to three different constraints, the objective is to find the minimum number of channels used in order to satisfy various numbers of demands from each cell. The proposed algorithm was tested on standard benchmark problems and the results obtained show the effectiveness of a simple yet efficient algorithm with the help of an improved shift mutation technique that are normally applied in evolutionary strategy.

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“…However, they are not feasible when tackling large instances of the problem [1], so several heuristic and metaheuristics methods [3] have also been proposed to deal with FAP. In particular, most of the current research in the FAP is based on using Memetic Algorithms (MAs) [28,31,36,49,55]. MAs [38,52] are a synergy of a population-based approach with separate individual learning or local improvement procedures for problem search.…”

Section: Introductionmentioning

confidence: 99%

Parallel hyperheuristics for the frequency assignment problem

2010

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This work presents a set of approaches used to deal with the frequency assignment problem (FAP), which is one of the key issues in the design of GSM networks. The used formulation of FAP is focused on aspects which are relevant for real-world GSM networks. A memetic algorithm, together with the specifically designed local search and variation operators, are presented. The memetic algorithm obtains good quality solutions but it must be adapted for each instance to be solved. A parallel hyperheuristic-based model was used to parallelize the approach and to avoid the requirement of the adaptation step of the memetic algorithm. The model is a hybrid algorithm which combines a parallel island-based scheme with a hyperheuristic approach. The main operation of the island-based model is kept, but the configurations of the memetic algorithms executed on each island are dynamically mapped. The model grants more computational resources to those configurations that show a more promising behavior. For this purpose two different criteria have been used in order to select the configurations. The first one is based on the improvements that each configuration is able to achieve along the executions. The second one tries to detect synergies among the configurations, i.e., detect which configurations obtain better solutions when they are cooperating. Computational results obtained for two different real-world instances of the FAP demonstrate the validity of the proposed model. The new designed schemes have made possible to improve the previously known best frequency plans for a real-world network.

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A memetic algorithm for channel assignment in wireless FDMA systems

Cited by 20 publications

References 18 publications

Solving large-scale real-world telecommunication problems using a grid-based genetic algorithm

Solving large-scale real-world telecommunication problems using a grid-based genetic algorithm

A permutation based technique for channel assignment problem

Parallel hyperheuristics for the frequency assignment problem

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