A Review on Genetic Algorithm Operations and Application in Telecommunication Routing

Singh, Neha; Chaurasia, Pawan Kumar

doi:10.26438/ijcse/v7i7.373377

Cited by 3 publications

(5 citation statements)

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“…Genetic algorithms were first developed by Professor Holland to simulate biological systems in computer analysis and construct the technology for genetic algorithms [38]. Subsequently, the basic principles of genetic algorithms, the concept of genetic programing (GP), neural networks, and other related topics were proposed.…”

Section: Methods and Research Designmentioning

confidence: 99%

Research on Green Building Design Optimization Based on Building Information Modeling and Improved Genetic Algorithm

Liu,

Ouyang,

Huang

et al. 2024

Advances in Civil Engineering

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The energy consumption of the construction industry has been increasing year by year, posing a huge challenge to China’s dual carbon goals of peaking carbon emissions and achieving carbon neutrality. The Chinese construction industry has huge potential for energy conservation and emission reduction, and the government has therefore put forward requirements for constructing green buildings and formulated strict evaluation standards. The carbon emissions of the construction industry involve various stages of the entire life cycle and are closely related to the green building design standards that meet the requirements. This article sets multiple objective functions based on the two dimensions of the carbon emissions of the entire life cycle of buildings and green building evaluation and uses the NSGA-II algorithm in genetic algorithms to optimize ten indicators selected from the two objectives. Based on this, building information modeling (BIM) modeling was carried out for an office building project in Southwest China, and energy consumption analysis and evaluation were conducted based on the project’s multidisciplinary model. The dialectical relationship between the carbon emissions of the entire life cycle of buildings and the green building evaluation values was discovered, and the optimized parameter combination scheme corresponding to the Pareto solution set was obtained, providing a reference for using improved genetic algorithms and BIM technology to optimize green building design.

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Section: Methods and Research Designmentioning

confidence: 99%

Research on Green Building Design Optimization Based on Building Information Modeling and Improved Genetic Algorithm

Liu,

Ouyang,

Huang

et al. 2024

Advances in Civil Engineering

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show abstract

“…The proposed work can be utilized in many applications affected by the field of optimization, such as computer networks, routing algorithms, wireless sensor networks, etc. Our focus in this paper will be routing algorithms, where efficient routing of packets through nodes is very important because it will find the path between two entities (two nodes) with the least amount of cost and disturbance [32]. The proposed modification to the genetic algorithm optimizes the distance since the proposed method (as opposed to existing approaches) takes into account network congestion when optimizing.…”

Section: Applications Of the Proposed Workmentioning

confidence: 99%

Oriented Crossover in Genetic Algorithms for Computer Networks Optimization

Rabee

Hussain

2023

Information

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Optimization using genetic algorithms (GA) is a well-known strategy in several scientific disciplines. The crossover is an essential operator of the genetic algorithm. It has been an active area of research to develop sustainable forms for this operand. In this work, a new crossover operand is proposed. This operand depends on giving an elicited description for the chromosome with a new structure for alleles of the parents. It is suggested that each allele has two attitudes, one attitude differs contrastingly with the other, and both of them complement the allele. Thus, in case where one attitude is good, the other should be bad. This is suitable for many systems which contain admired parameters and unadmired parameters. The proposed crossover would improve the desired attitudes and dampen the undesired attitudes. The proposed crossover can be achieved in two stages: The first stage is a mating method for both attitudes in one parent to improving one attitude at the expense of the other. The second stage comes after the first improvement stage for mating between different parents. Hence, two concurrent steps for improvement would be applied. Simulation experiments for the system show improvement in the fitness function. The proposed crossover could be helpful in different fields, especially to optimize routing algorithms and network protocols, an application that has been tested as a case study in this work.

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“…The proposed work in this article supposes to be for many applications in the field of optimization, such as Computer networks, Routing algorithms, wireless sensor networks … etc. Our interest in this paper will be routing algorithms, where efficiently routing packets through nodes is very important because it will find the path between two entities (two nodes) with the least amount of disturbance [20]. The proposed modification to the genetic algorithm improves the distance, where this proposed method differs from others in that it takes into account network congestion when optimizing.…”

Section: Applications Of the Proposed Workmentioning

confidence: 99%

“…The cost function for each individual has been calculated after converting the binary to decimal values. The binary crossover was implemented for five generations to test the four Eq (19)(20)(21)(22).…”

Section: Genetic Algorithm Parametersmentioning

confidence: 99%

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Oriented Crossover in Genetic Algorithms for Computer Networks Optimization

Rabee¹,

Hussain²

2023

Preprint

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Optimization using Genetic Algorithms (GA) is a well-known strategy in several scientific disciplines. The crossover is an essential operator of the Genetic Algorithm. It has been an active area of research to develop sustainable forms for this operand. In this work, a new crossover operand is proposed. This operand depends on giving an elicited description for the chromosome with a new structure for alleles of the parents. It is suggested that each allele has two attitudes, one attitude differs contrastingly with the other, and both of them complement the allele. Thus, in case of one attitude is good, the other should be bad. This is suitable for many systems which contain admired parameters and unadmired parameters. The proposed crossover would improve the desired attitudes and damp the undesired attitudes. The proposed crossover can be achieved in two stages: the first stage is a mating method for both attitudes in one parent to improving one attitude at the expense of the other. The second stage comes after the first improvement stage for mating between different parents. Hence, two concurrent steps for improvement would be applied. Simulation experiments for the system shows improvement in the fitness function. The proposed crossover could be helpful in different fields, especially to optimize routing algorithms and network protocols, an application that has been tested as a case study in this work.

show abstract

A Review on Genetic Algorithm Operations and Application in Telecommunication Routing

Cited by 3 publications

References 0 publications

Research on Green Building Design Optimization Based on Building Information Modeling and Improved Genetic Algorithm

Research on Green Building Design Optimization Based on Building Information Modeling and Improved Genetic Algorithm

Oriented Crossover in Genetic Algorithms for Computer Networks Optimization

Oriented Crossover in Genetic Algorithms for Computer Networks Optimization

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