An improvement of genetic algorithm for optimization problem

Pravesjit, Sakkayaphop; Kantawong, Krittika

doi:10.1109/icdamt.2017.7904966

Cited by 12 publications

(8 citation statements)

References 7 publications

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“…• Fitness Evaluation Function: Let fitness f i represent each individual's adaptability in N [34]. In this paper, the formula to calculate the GA-BPTS individuals' fitness in N is given by…”

Section: ) Ga Based Bpts Phase Factors Search Schemementioning

confidence: 99%

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Genetic Algorithm Based Bilayer PTS Scheme for Peak-to-Average Power Ratio Reduction of FBMC/OQAM Signal

Zhao

Yang

et al. 2020

IEEE Access

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Partial transmit sequence (PTS) scheme has been well applied to reduce the high peak-toaverage power ratio (PAPR) of the orthogonal frequency division multiplexing (OFDM) signal. However, due to the signal structure differences between the filter bank multicarrier and offset quadrature amplitude modulation (FBMC/OQAM) signal and the OFDM signal, the conventional PTS scheme is not applicable to the FBMC/OQAM signal. Considering the PAPR reduction issue for the FBMC/OQAM signal, this paper proposes a genetic algorithm (GA) based bilayer partial transmit sequence (GA-BPTS) scheme. In order to reduce the computational complexity, the proposed scheme continues to partition each subblock, transforming the single layer structure of the conventional PTS into a bilayer phase factor search structure, and introduces a penalty threshold. Then the suboptimal phase factor vector is obtained by using the GA. Meanwhile, before PAPR reduction processing, aided by the proposed prototype filter which has the better performance of out-of-band attenuation than the PHYDAYS filter, the GA-BPTS scheme can effectively reduce the PAPR of the FBMC/OQAM signal. The simulations have confirmed that the proposed scheme not only provides an excellent PAPR performance but also decreases the computational complexity compared with the conventional PTS scheme. INDEX TERMS Bilayer partial transmit sequence (PTS), filter bank multicarrier and offset quadrature amplitude modulation (FBMC/OQAM), genetic algorithm (GA), peak-to-average power ratio (PAPR) reduction.

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Section: ) Ga Based Bpts Phase Factors Search Schemementioning

confidence: 99%

“…However, the fixed probability of P c and P m may result in poor performance of convergence speed and the quality of solution. In order to improve the optimization ability of the GA-BPTS scheme, the adaptive genetic operators [34] are applied to escape from the local optimum. The expressions are given as…”

Section: ) Ga Based Bpts Phase Factors Search Schemementioning

confidence: 99%

Genetic Algorithm Based Bilayer PTS Scheme for Peak-to-Average Power Ratio Reduction of FBMC/OQAM Signal

Zhao

Yang

et al. 2020

IEEE Access

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“…In addition, among all kinds of parameters optimization methods, Particle Swarm Optimization (PSO) algorithm [41]- [43], Genetic Algorithm (GA) [44]- [46], and in recent years, Lu Cheng et al [47], [48] newly proposed methods such as Global/local Linked Driven Optimization Strategy (GLDOS) and Improved Decomposed-Coordinated Kriging Modeling Strategy (IDCKMS) are representative. The above optimization methods can efficiently and accurately optimize and solve specific objective function models; However, for problems that need to first construct an optimized objective function model through experiments, and then optimize its parameters (Such as this paper will optimize the control parameters of sine rotating puncture, which belongs to this kind of optimization problem), the experimental statistical analysis method is generally used for optimization analysis.…”

Section: Parameter Optimization Experimentsmentioning

confidence: 99%

Study on the Control Method and Optimization Experiment of Prostate Soft Tissue Puncture

Zhang

Liu

2020

IEEE Access

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In the treatment of prostate cancer patients, surgery of radioactive seed implantation with the puncture robots is an effective treatment method. However, when the puncture needle enters the lesion tissue, there are complicated forces between the needle body and the soft tissue, which leads to the drift of the prostate and the deflection of the puncture needle, thereby affecting the puncture accuracy. In order to improve the positioning accuracy and ensure the best treatment effect, a sine rotation continuous puncture control method was proposed in this paper. First, by analyzing the interaction between the puncture needle and the soft tissue, the force balance equation and the deflection equation were established, according to the equations, it could be known that puncture friction is the main factor affecting the deflection of the puncture needle. Second, combined with the influence of puncture friction and the research on the theory of rotation puncture, the sine rotation puncture method was compared with the direct puncture method and the existing rotation puncture method; Observed with a 4D Color Doppler Ultrasound to verify the feasibility of the rotating puncture theory and the effectiveness of the sine rotation puncture method. Third, through the establishment of Euler Beam model, rotation angle analysis and puncture velocity test analysis, the influence of dynamic parameters of this method on the puncture accuracy was discussed, the optimization range of each factor was obtained; The experiment was designed by the quadratic regression orthogonal combination theory, the experiment process was observed and recorded by a 3D X-ray scanner, the regression equations were established between experiment factors and experiment indicators with the Design-Expert, and the best parameter combinations were acquired through optimization. Last, comparison tests and verification test were carried out to verify the rationality and reliability of the optimized sine rotation puncture control method.

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“…In recent years, researchers have adjusted GAs to increase efficiency for application to new complex systems. For instance, researchers have focused on improving the selection operator to find optimal solutions to the multicast routing problem [1], performing a local search with the best offspring in a generation to quickly converge on the global optimum [7], improving the population initialization and crossover operator to segment magnetic resonance images [14], applying the Gaussian function with crossover and mutation to reduce computation time [15], and solving the traveling salesman problem by combining a GA and two local optimization strategies [16].…”

Section: Motivation and Related Workmentioning

confidence: 99%

Analyzing the Performance of the Multiple-Searching Genetic Algorithm to Generate Test Cases

2020

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Software testing using traditional genetic algorithms (GAs) minimizes the required number of test cases and reduces the execution time. Currently, GAs are adapted to enhance performance when finding optimal solutions. The multiple-searching genetic algorithm (MSGA) has improved upon current GAs and is used to find the optimal multicast routing in network systems. This paper presents an analysis of the optimization of test case generations using the MSGA by defining suitable values of MSGA parameters, including population size, crossover operator, and mutation operator. Moreover, in this study, we compare the performance of the MSGA with a traditional GA and hybrid GA (HGA). The experimental results demonstrate that MSGA reaches the maximum executed branch statements in the lowest execution time and the smallest number of test cases compared to the GA and HGA.

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An improvement of genetic algorithm for optimization problem

Cited by 12 publications

References 7 publications

Genetic Algorithm Based Bilayer PTS Scheme for Peak-to-Average Power Ratio Reduction of FBMC/OQAM Signal

Genetic Algorithm Based Bilayer PTS Scheme for Peak-to-Average Power Ratio Reduction of FBMC/OQAM Signal

Study on the Control Method and Optimization Experiment of Prostate Soft Tissue Puncture

Analyzing the Performance of the Multiple-Searching Genetic Algorithm to Generate Test Cases

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