Evolutionary algorithms for solving the automatic cell planning problem: a survey

Luna, Francisco; Durillo, Juan J.; Nebro, Antonio J.; Alba, Enrique

doi:10.1080/03052150903426850

Cited by 25 publications

(7 citation statements)

References 65 publications

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“…The metaheuristic techniques have been proved to be very powerful in finding optimal or near-optimal solutions due to their heuristic nature (Blum and Roli 2003;Luna et al 2010). The metaheuristic techniques have been proved to be very powerful in finding optimal or near-optimal solutions due to their heuristic nature (Blum and Roli 2003;Luna et al 2010).…”

Section: Techniques For Optimization Problems In Production Decision-mentioning

confidence: 99%

Intelligent Decision-making Models for Production and Retail Operations

Guo¹

2016

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Section: Techniques For Optimization Problems In Production Decision-mentioning

confidence: 99%

Intelligent Decision-making Models for Production and Retail Operations

Guo¹

2016

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“…Frequency planning is a widely known NP-hard problem introduced in Metzger (1970). Among the large number of studies focussed on FAP, there are some complete studies performed by several authors recently (Aardal et al, 2007;Eisenblätter, 2001;Luna et al, 2010). Moreover, different approaches and strategies have been applied to the resolution of different versions of the problem.…”

Section: Related Workmentioning

confidence: 99%

Evolutionary team based on different metaheuristics for solving a real-world problem in the telecommunication domain

Chaves-González

Vega‐Rodríguez

2014

Engineering Computations

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Article information:To cite this document: Jose M. Chaves-Gonzalez Miguel A. Vega-Rodríguez , (2014),"Evolutionary team based on different metaheuristics for solving a real-world problem in the telecommunication domain", Engineering Computations, Vol. 31 Iss 7 pp. 1550 -1581 Permanent link to this document: http://dx. AbstractPurpose -The purpose of this paper is to study the use of a heterogeneous and evolutionary team approach based on different sources of knowledge to address a real-world problem within the telecommunication domain: the frequency assignment problem (FAP). Evolutionary algorithms have been proved as very suitable strategies when they are used to solve NP-hard optimization problems. However, these algorithms can find difficulties when they fall into local minima and the generation of high-quality solutions when tacking real-world instances of the problem is computationally very expensive. In this scenario, the use of a heterogeneous parallel team represents a very interesting approach. Design/methodology/approach -The results have been validated by using two real-world telecommunication instances which contain real information about two GSM networks. Contrary to most of related publications, this paper is focussed on aspects which are relevant for real communication networks. Moreover, due to the stochastic nature of metaheuristics, the results are validated through a formal statistical analysis. This analysis is divided in two stages: first, a complete statistical study, and after that, a full comparative study against results previously published. Findings -Comparative study shows that a heterogeneous evolutionary proposal obtains better results than proposals which are based on a unique source of knowledge. In fact, final results provided in the work surpass the results of other relevant studies previously published in the literature. Originality/value -The paper provides a complete study of the contribution provided by the different metaheuristics included in the team and the impact of using different sources of evolutionary knowledge when the system is applied to solve a real-world FAP problem. The conclusions obtained in this study represent an original contribution never reached before for FAP.

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“…Smart antennas can help in improving the communication system performance by increasing channel capacity and spectrum efficiency, extending range coverage, steering multiple beams to track many mobiles, and compensating electronically for aperture distortion [7]. For the most part of BTS solutions used in the electrical sector, the RF signal is propagated by a collinear array with an omnidirectional propagation [8]. In the location where the researches generated this article (Pernambuco, Brazil), an antenna array of collinear dipoles is used by the electricity distribution company (Neoenergia) in each of the Base Transceiver Stations.…”

Section: Introductionmentioning

confidence: 99%

Application of the Base Transceiver Station with Smart Antennas in the Power Distribution Sector

Kleinau

Melo

et al. 2021

International Journal of Antennas and Propagation

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The use of distribution automation systems has grown significantly in electricity companies in recent years. The main reason for this is the need to have a smarter network, in order to reduce the time of power interruption. For such applications, communication using radio frequency is preferred because this solution is more reliable than 3G/4G and cheaper than fiber optics. In this context, it is of utmost importance to have a more efficient base transceiver station (BTS) that can cover the communication of a larger area. In this paper, the mathematical concepts of an intelligent antenna array, as well as the logical operation of an intelligent radiation system controller, are presented. Such system receives as inputs the geographic coordinates of network elements and automatically feeds an intelligent Yagi–Uda antenna array with the appropriate parameters, in order to optimize the radiation pattern into the desired directions. The presented model uses a stochastic optimization method to automatically achieve a set of optimal electrical parameters to excite the array and efficiently direct its beams in a fully controlled way. Thus, the results obtained indicate that the proposed intelligent scheme allows the energy optimization of the antenna system, reducing in 61% the number of BTS needed to cover the same area, when compared to traditional collinear antenna systems.

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Evolutionary algorithms for solving the automatic cell planning problem: a survey

Cited by 25 publications

References 65 publications

Intelligent Decision-making Models for Production and Retail Operations

Intelligent Decision-making Models for Production and Retail Operations

Evolutionary team based on different metaheuristics for solving a real-world problem in the telecommunication domain

Application of the Base Transceiver Station with Smart Antennas in the Power Distribution Sector

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