How Distance Based Parameter Adaptation Affects Population Diversity

2018 ◽  
pp. 307-319
Author(s):  
Adam Viktorin ◽  
Roman Senkerik ◽  
Michal Pluhacek ◽  
Tomas Kadavy
Keyword(s):  
Population Diversity ◽  
Parameter Adaptation

scholarly journals Ranking-based hierarchical random mutation in differential evolution

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0245887
Author(s):  
Xuxu Zhong ◽  
Meijun Duan ◽  
Peng Cheng
Keyword(s):  
Individual Differences ◽  
Differential Evolution ◽  
Control Parameter ◽  
Population Diversity ◽  
Convergence Speed ◽  
Mutation Operator ◽  
Random Mutation ◽  
Parameter Adaptation ◽  
Fitness Value ◽  
Control Parameter Adaptation

In order to improve the performance of differential evolution (DE), this paper proposes a ranking-based hierarchical random mutation in differential evolution (abbreviated as RHRMDE), in which two improvements are presented. First, RHRMDE introduces a hierarchical random mutation mechanism to apply the classic “DE/rand/1” and its variant on the non-inferior and inferior group determined by the fitness value. The non-inferior group employs the traditional mutation operator “DE/rand/1” with global and random characteristics, which increases the global exploration ability and population diversity. The inferior group uses the improved mutation operator “DE/rand/1” with elite and random characteristics, which enhances the local exploitation ability and convergence speed. Second, the control parameter adaptation of RHRMDE not only considers the complexity differences of various problems but also takes individual differences into account. The proposed RHRMDE is compared with five DE variants and five non-DE algorithms on 32 universal benchmark functions, and the results show that the RHRMDE is superior over the compared algorithms.

Genetic Population Diversity of Aedes caspius in Southern Provinces of Iran

2018 ◽  
Vol 111 (1) ◽  
pp. 31-37 ◽  
Author(s):  
S DOOSTI ◽  
MR YAGHOOBI-ERSHADI ◽  
MM SEDAGHAT ◽  
SH MOOSA-KAZEMI ◽  
K AKBARZADEH ◽  
...  
Keyword(s):  
Population Diversity ◽  
Genetic Population ◽  
Aedes Caspius

AO-BBO: A Novel Optimization Algorithm and Its Application in Plant Drug Extraction

2019 ◽  
Vol 19 (2) ◽  
pp. 139-145 ◽  
Author(s):  
Bote Lv ◽  
Juan Chen ◽  
Boyan Liu ◽  
Cuiying Dong
Keyword(s):  
Optimization Algorithm ◽  
Learning Strategy ◽  
Optimal Solution ◽  
Population Diversity ◽  
Global Optimal Solution ◽  
Plant Medicine ◽  
Suitability Index ◽  
Sensing Model ◽  
Local Optimal Solution ◽  
Global Optimal

<P>Introduction: It is well-known that the biogeography-based optimization (BBO) algorithm lacks searching power in some circumstances. </P><P> Material & Methods: In order to address this issue, an adaptive opposition-based biogeography-based optimization algorithm (AO-BBO) is proposed. Based on the BBO algorithm and opposite learning strategy, this algorithm chooses different opposite learning probabilities for each individual according to the habitat suitability index (HSI), so as to avoid elite individuals from returning to local optimal solution. Meanwhile, the proposed method is tested in 9 benchmark functions respectively. </P><P> Result: The results show that the improved AO-BBO algorithm can improve the population diversity better and enhance the search ability of the global optimal solution. The global exploration capability, convergence rate and convergence accuracy have been significantly improved. Eventually, the algorithm is applied to the parameter optimization of soft-sensing model in plant medicine extraction rate. Conclusion: The simulation results show that the model obtained by this method has higher prediction accuracy and generalization ability.</P>

scholarly journals Internal Leakage Fault Detection and Tolerant Control of Single-Rod Hydraulic Actuators

2014 ◽  
Vol 2014 ◽  
pp. 1-14 ◽  
Author(s):  
Jianyong Yao ◽  
Guichao Yang ◽  
Dawei Ma
Keyword(s):  
Fault Detection ◽  
Simple Structure ◽  
Control Method ◽  
Fault Tolerant ◽  
Parameter Adaptation ◽  
Servo Systems ◽  
Hydraulic Actuators ◽  
Quadratic Lyapunov Functions ◽  
Safety And Reliability ◽  
Hydraulic Servo

The integration of internal leakage fault detection and tolerant control for single-rod hydraulic actuators is present in this paper. Fault detection is a potential technique to provide efficient condition monitoring and/or preventive maintenance, and fault tolerant control is a critical method to improve the safety and reliability of hydraulic servo systems. Based on quadratic Lyapunov functions, a performance-oriented fault detection method is proposed, which has a simple structure and is prone to implement in practice. The main feature is that, when a prescribed performance index is satisfied (even a slight fault has occurred), there is no fault alarmed; otherwise (i.e., a severe fault has occurred), the fault is detected and then a fault tolerant controller is activated. The proposed tolerant controller, which is based on the parameter adaptive methodology, is also prone to realize, and the learning mechanism is simple since only the internal leakage is considered in parameter adaptation and thus the persistent exciting (PE) condition is easily satisfied. After the activation of the fault tolerant controller, the control performance is gradually recovered. Simulation results on a hydraulic servo system with both abrupt and incipient internal leakage fault demonstrate the effectiveness of the proposed fault detection and tolerant control method.

scholarly journals Knowledge-guided multiobjective particle swarm optimization with fusion learning strategies

2021 ◽  
Author(s):  
Wei Li ◽  
Xiang Meng ◽  
Ying Huang ◽  
Soroosh Mahmoodi
Keyword(s):  
Particle Swarm Optimization ◽  
Learning Strategies ◽  
Learning Strategy ◽  
Particle Swarm ◽  
Population Diversity ◽  
Selection Strategy ◽  
Rapid Loss ◽  
Solution Quality ◽  
Swarm Optimization ◽  
Multiobjective Particle Swarm Optimization

AbstractMultiobjective particle swarm optimization (MOPSO) algorithm faces the difficulty of prematurity and insufficient diversity due to the selection of inappropriate leaders and inefficient evolution strategies. Therefore, to circumvent the rapid loss of population diversity and premature convergence in MOPSO, this paper proposes a knowledge-guided multiobjective particle swarm optimization using fusion learning strategies (KGMOPSO), in which an improved leadership selection strategy based on knowledge utilization is presented to select the appropriate global leader for improving the convergence ability of the algorithm. Furthermore, the similarity between different individuals is dynamically measured to detect the diversity of the current population, and a diversity-enhanced learning strategy is proposed to prevent the rapid loss of population diversity. Additionally, a maximum and minimum crowding distance strategy is employed to obtain excellent nondominated solutions. The proposed KGMOPSO algorithm is evaluated by comparisons with the existing state-of-the-art multiobjective optimization algorithms on the ZDT and DTLZ test instances. Experimental results illustrate that KGMOPSO is superior to other multiobjective algorithms with regard to solution quality and diversity maintenance.

scholarly journals An Improved Whale Optimization Algorithm for the Traveling Salesman Problem

Symmetry ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 48
Author(s):  
Jin Zhang ◽  
Li Hong ◽  
Qing Liu
Keyword(s):  
Traveling Salesman Problem ◽  
Optimization Algorithm ◽  
Optimization Problems ◽  
Relevant Literature ◽  
Population Diversity ◽  
Traveling Salesman ◽  
Whale Optimization Algorithm ◽  
Neighborhood Search ◽  
Whale Optimization ◽  
The Traveling Salesman Problem

The whale optimization algorithm is a new type of swarm intelligence bionic optimization algorithm, which has achieved good optimization results in solving continuous optimization problems. However, it has less application in discrete optimization problems. A variable neighborhood discrete whale optimization algorithm for the traveling salesman problem (TSP) is studied in this paper. The discrete code is designed first, and then the adaptive weight, Gaussian disturbance, and variable neighborhood search strategy are introduced, so that the population diversity and the global search ability of the algorithm are improved. The proposed algorithm is tested by 12 classic problems of the Traveling Salesman Problem Library (TSPLIB). Experiment results show that the proposed algorithm has better optimization performance and higher efficiency compared with other popular algorithms and relevant literature.

Portfolio simplification arising from a century of change in salmon population diversity and artificial production

2021 ◽  
Author(s):  
Michael H. H. Price ◽  
Jonathan W. Moore ◽  
Brendan M. Connors ◽  
Kyle L. Wilson ◽  
John D. Reynolds
Keyword(s):  
Population Diversity ◽  
Salmon Population

scholarly journals Genetic diversity and population structure of Plasmodium falciparum in Nigeria: insights from microsatellite loci analysis

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Fehintola V. Ajogbasile ◽  
Adeyemi T. Kayode ◽  
Paul E. Oluniyi ◽  
Kazeem O. Akano ◽  
Jessica N. Uwanibe ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Plasmodium Falciparum ◽  
Population Structure ◽  
Microsatellite Loci ◽  
Control Strategies ◽  
Population Diversity ◽  
Parasite Population ◽  
Nested Polymerase Chain Reaction ◽  
Public Health Burden ◽  
Genetic Diversity And Structure

Abstract Background Malaria remains a public health burden especially in Nigeria. To develop new malaria control and elimination strategies or refine existing ones, understanding parasite population diversity and transmission patterns is crucial. Methods In this study, characterization of the parasite diversity and structure of Plasmodium falciparum isolates from 633 dried blood spot samples in Nigeria was carried out using 12 microsatellite loci of P. falciparum. These microsatellite loci were amplified via semi-nested polymerase chain reaction (PCR) and fragments were analysed using population genetic tools. Results Estimates of parasite genetic diversity, such as mean number of different alleles (13.52), effective alleles (7.13), allelic richness (11.15) and expected heterozygosity (0.804), were high. Overall linkage disequilibrium was weak (0.006, P < 0.001). Parasite population structure was low (Fst: 0.008–0.105, AMOVA: 0.039). Conclusion The high level of parasite genetic diversity and low population structuring in this study suggests that parasite populations circulating in Nigeria are homogenous. However, higher resolution methods, such as the 24 SNP barcode and whole genome sequencing, may capture more specific parasite genetic signatures circulating in the country. The results obtained can be used as a baseline for parasite genetic diversity and structure, aiding in the formulation of appropriate therapeutic and control strategies in Nigeria.

Sign in / Sign up

Export Citation Format

Share Document