scholarly journals Diversity Measures for Niching Algorithms

Algorithms ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 36
Author(s):  
Jonathan Mwaura ◽  
Andries P. Engelbrecht ◽  
Filipe V. Nepomuceno
Keyword(s):  
Critical Factor ◽  
Search Space ◽  
Particle Swarm Optimisation ◽  
Diversity Measures ◽  
Low Diversity ◽  
Global Optima ◽  
Multimodal Problems ◽  
High Diversity ◽  
Single Objective ◽  
Exploration Phase

Multimodal problems are single objective optimisation problems with multiple local and global optima. The objective of multimodal optimisation is to locate all or most of the optima. Niching algorithms are the techniques utilised to locate these optima. A critical factor in determining the success of niching algorithms is how well the search space is covered by the candidate solutions. For niching algorithms, high diversity during the exploration phase will facilitate location and identification of many solutions while a low diversity means that the candidate solutions are clustered at optima. This paper provides a review of measures used to quantify diversity, and how they can be utilised to quantify the dispersion of both the candidate solutions and the solutions of niching algorithms (i.e., found optima). The investigated diversity measures are then used to evaluate the distribution of candidate solutions and solutions when the enhanced species-based particle swarm optimisation (ESPSO) algorithm is utilised to optimise a selected set of multimodal problems.

Recent Rapid Climate Changes in Antarctic and their Influence on Low Diversity Ecosystems

2010 ◽  
Vol 17 (1) ◽  
pp. 17-30 ◽  
Author(s):  
Katarzyna J. Chwedorzewska
Keyword(s):  
Environmental Variables ◽  
Climate Changes ◽  
Biological Significance ◽  
Global Changes ◽  
Factors Affecting ◽  
Low Diversity ◽  
Main Factors ◽  
The Antarctic ◽  
High Diversity ◽  
Temperature Water

ABSTRACTThe geographic position, astronomic factors (e.g. the Earth’s maximum distance from the Sun during winter), ice cover and altitude are the main factors affecting the climate of the Antarctic, which is the coldest place on Earth. Parts of Antarctica are facing the most rapid rates of anthropogenic climate change currently seen on the planet. Climate changes are occurring throughout Antarctica, affecting three major groups of environmental variables of considerable biological significance: temperature, water, UV-B radiation.Low diversity ecosystems are expected to be more vulnerable to global changes than high diversity ecosystems

Diversity and community structure of Ephemeroptera in freshwater stream of Megamalai hills, Tamil Nadu, India

ENTOMON ◽  
2021 ◽  
Vol 46 (4) ◽  
pp. 279-284
Author(s):  
S. Barathy ◽  
T. Sivaruban ◽  
Srinivasan Pandiarajan ◽  
Isack Rajasekaran ◽  
M. Bernath Rosi
Keyword(s):  
Community Structure ◽  
Species Diversity ◽  
Air Temperature ◽  
Tamil Nadu ◽  
Dominant Species ◽  
Diversity Indices ◽  
Low Diversity ◽  
Freshwater Stream ◽  
Species Diversity Indices ◽  
High Diversity

In the study on the diversity and community structure of Ephemeroptera in the freshwater stream of Chinnasuruli falls on Megamalai hills, a total of 523 specimens belonging to thirteen genera and five families were collected in six month periods. Of the five families, Teloganodidae and Leptophlebiidae exhibited high diversity and Caenidae showed low diversity. Choroterpes alagarensis (Leptophlebiidae) is the most dominant species. Diversity indices such as Shannon and Simpson indices showed that diversity was maximum in November and December and it was minimum in August and January. Canonical Correspondence Analysis revealed that rainfall, water flow, turbidity, and air temperature were the major stressors in affecting the Ephemeropteran community structure.

Genetic Algorithms and Multimodal Search

2011 ◽  
pp. 231-249
Author(s):  
Marcos Gestal ◽  
José Manuel Vázquez Naya ◽  
Norberto Ezquerra
Keyword(s):  
Genetic Algorithms ◽  
Evolutionary Computation ◽  
Unique Solution ◽  
Real World ◽  
Multiple Solutions ◽  
Global Solutions ◽  
Search Space ◽  
The Real ◽  
Local Solutions ◽  
Multimodal Problems

Traditionally, the Evolutionary Computation (EC) techniques, and more specifically the Genetic Algorithms (GAs), have proved to be efficient when solving various problems; however, as a possible lack, the GAs tend to provide a unique solution for the problem on which they are applied. Some non global solutions discarded during the search of the best one could be acceptable under certain circumstances. Most of the problems at the real world involve a search space with one or more global solutions and multiple local solutions; this means that they are multimodal problems and therefore, if it is desired to obtain multiple solutions by using GAs, it would be necessary to modify their classic functioning outline for adapting them correctly to the multimodality of such problems. The present chapter tries to establish, firstly, the characterisation of the multimodal problems will be attempted. A global view of some of the several approaches proposed for adapting the classic functioning of the GAs to the search of mu ltiple solutions will be also offered. Lastly, the contributions of the authors and a brief description of several practical cases of their performance at the real world will be also showed.

scholarly journals Measuring the shape of the biodiversity-disease relationship across systems reveals new findings and key gaps

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Fletcher W. Halliday ◽  
Jason R. Rohr
Keyword(s):  
Spatial Scale ◽  
Parasite Species ◽  
Biodiversity Loss ◽  
Field Studies ◽  
New Findings ◽  
Small Scales ◽  
Low Diversity ◽  
Wildlife Populations ◽  
Dilution Effects ◽  
High Diversity

Abstract Diverse host communities commonly inhibit the spread of parasites at small scales. However, the generality of this effect remains controversial. Here, we present the analysis of 205 biodiversity–disease relationships on 67 parasite species to test whether biodiversity–disease relationships are generally nonlinear, moderated by spatial scale, and sensitive to underrepresentation in the literature. Our analysis of the published literature reveals that biodiversity–disease relationships are generally hump-shaped (i.e., nonlinear) and biodiversity generally inhibits disease at local scales, but this effect weakens as spatial scale increases. Spatial scale is, however, related to study design and parasite type, highlighting the need for additional multiscale research. Few studies are unrepresentative of communities at low diversity, but missing data at low diversity from field studies could result in underreporting of amplification effects. Experiments appear to underrepresent high-diversity communities, which could result in underreporting of dilution effects. Despite context dependence, biodiversity loss at local scales appears to increase disease, suggesting that at local scales, biodiversity loss could negatively impact human and wildlife populations.

scholarly journals Success History-Based Adaptive Differential Evolution Using Turning-Based Mutation

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1565 ◽  
Author(s):  
Xingping Sun ◽  
Linsheng Jiang ◽  
Yong Shen ◽  
Hongwei Kang ◽  
Qingyi Chen
Keyword(s):  
Differential Evolution ◽  
Clustering Analysis ◽  
Numerical Optimization ◽  
Optimization Algorithms ◽  
Search Space ◽  
Population Diversity ◽  
Convergence Of Algorithms ◽  
Adaptive Differential Evolution ◽  
Complex Methods ◽  
Single Objective

Single objective optimization algorithms are the foundation of establishing more complex methods, like constrained optimization, niching and multi-objective algorithms. Therefore, improvements to single objective optimization algorithms are important because they can impact other domains as well. This paper proposes a method using turning-based mutation that is aimed to solve the problem of premature convergence of algorithms based on SHADE (Success-History based Adaptive Differential Evolution) in high dimensional search space. The proposed method is tested on the Single Objective Bound Constrained Numerical Optimization (CEC2020) benchmark sets in 5, 10, 15, and 20 dimensions for all SHADE, L-SHADE, and jSO algorithms. The effectiveness of the method is verified by population diversity measure and population clustering analysis. In addition, the new versions (Tb-SHADE, TbL-SHADE and Tb-jSO) using the proposed turning-based mutation get apparently better optimization results than the original algorithms (SHADE, L-SHADE, and jSO) as well as the advanced DISH and the jDE100 algorithms in 10, 15, and 20 dimensional functions, but only have advantages compared with the advanced j2020 algorithm in 5 dimensional functions.

scholarly journals Insights into Exploration and Exploitation Power of Optimization Algorithm Using DSCTool

Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1474
Author(s):  
Peter Korošec ◽  
Tome Eftimov
Keyword(s):  
Statistical Analysis ◽  
Web Service ◽  
Optimization Algorithm ◽  
Optimization Algorithms ◽  
Search Space ◽  
Exploration And Exploitation ◽  
Learning Tool ◽  
Additional Information ◽  
E Learning ◽  
Single Objective

When making statistical analysis of single-objective optimization algorithms’ performance, researchers usually estimate it according to the obtained optimization results in the form of minimal/maximal values. Though this is a good indicator about the performance of the algorithm, it does not provide any information about the reasons why it happens. One possibility to get additional information about the performance of the algorithms is to study their exploration and exploitation abilities. In this paper, we present an easy-to-use step by step pipeline that can be used for performing exploration and exploitation analysis of single-objective optimization algorithms. The pipeline is based on a web-service-based e-Learning tool called DSCTool, which can be used for making statistical analysis not only with regard to the obtained solution values but also with regard to the distribution of the solutions in the search space. Its usage does not require any special statistic knowledge from the user. The gained knowledge from such analysis can be used to better understand algorithm’s performance when compared to other algorithms or while performing hyperparameter tuning.

scholarly journals Cognitive Bare Bones Particle Swarm Optimisation with Jumps

2016 ◽  
Vol 7 (1) ◽  
pp. 1-31 ◽  
Author(s):  
Mohammad Majid al-Rifaie ◽  
Tim Blackwell
Keyword(s):  
Probability Distribution ◽  
Particle Swarm ◽  
Search Space ◽  
Particle Swarm Optimisation ◽  
Early Stages ◽  
Bare Bones

The ‘bare bones' (BB) formulation of particle swarm optimisation (PSO) was originally advanced as a model of PSO dynamics. The idea was to model the forces between particles with sampling from a probability distribution in the hope of understanding swarm behaviour with a conceptually simpler particle update rule. ‘Bare bones with jumps' (BBJ) proposes three significant extensions to the BB algorithm: (i) two social neighbourhoods, (ii) a tuneable parameter that can advantageously bring the swarm to the ‘edge of collapse' and (iii) a component-by-component probabilistic jump to anywhere in the search space. The purpose of this paper is to investigate the role of jumping within a specific BBJ algorithm, cognitive BBJ (cBBJ). After confirming the effectiveness of cBBJ, this paper finds that: jumping in one component only is optimal over the 30 dimensional benchmarks of this study; that a small per particle jump probability of 1/30 works well for these benchmarks; jumps are chiefly beneficial during the early stages of optimisation and finally this work supplies evidence that jumping provides escape from regions surrounding sub-optimal minima.

Changes in colonial development, intraspecific heterochrony, morphological integration, and character heritabilities in two populations of the bryozoan species Batostoma jamesi from the Kope Formation (Upper Ordovician, Cincinnatian)

2002 ◽  
Vol 76 (2) ◽  
pp. 197-210 ◽  
Author(s):  
Joseph F. Pachut ◽  
Margaret M. Fisherkeller
Keyword(s):  
Colony Growth ◽  
Early Growth ◽  
Morphological Integration ◽  
Growth Stages ◽  
Stabilizing Selection ◽  
Upper Ordovician ◽  
Surface Areas ◽  
Low Diversity ◽  
Kope Formation ◽  
High Diversity

Populations of the Upper Ordovician trepostome bryozoan Batostoma jamesi were collected from two different paleoenvironmental settings in the Kope Formation of southeastern Indiana. Within each colony and population, morphologic changes were analyzed during colony growth, or astogeny. Morphological measurements of zooecia, mesozooecia, and acanthostyles display similar patterns of change during colony growth in both populations but magnitudes are generally larger in the high diversity population.Canonical variates analyses provided multivariate confirmation of univariate character differences found within each population. Statistically significant multivariate morphological differences between growth stages persist even if assignments of colonies to populations are ignored. Results suggest different potentials for altering growth trajectories in different environments with early growth stage flexibility in colonies from lower diversity settings and later-stage flexibility in colonies from higher diversity settings.Heterochronic changes occur between species populations. Relative to the high-diversity population, the low-diversity population displays the following: 1) progenesis and hypermorphosis for zooecia, reflecting the ability to exist over a broader range of areal densities and surface areas than in populations from high-diversity associations; 2) postdisplacement and progenesis for mesozooecia, producing mature mesozooecial densities earlier in growth and at smaller sizes while the onset of mesozooecial development is delayed; and 3) acceleration, predisplacement, and progenesis for acanthostyles, resulting in a more rapid rate of development, an earlier onset of style development and more styles, and an earlier time of maturation, respectively.The estimated level of morphological integration is higher in the high diversity population regardless of stage of colony growth. Within populations, integration is stronger during early growth stages in colonies from high diversity settings and during later growth stages in colonies from low diversity settings. Character heritabilities are high in both diversity-level populations, suggesting that these patterns of morphological integration were not the result of non-heritable phenotypic plasticity. Mean heritability is greater in the high diversity population and differs statistically only between the late growth stages of populations. Patterns of morphological integration may result from differing levels of stabilizing selection in different environments. Depending on the timing of selection, these different levels of integration are capable of affecting the outcome of selection on species populations.

Blacks Mountain Experimental Forest: bark beetle responses to differences in forest structure and the application of prescribed fire in interior ponderosa pineThis article is one of a selection of papers from the Special Forum on Ecological Studies in Interior Ponderosa Pine — First Findings from Blacks Mountain Interdisciplinary Research.

2008 ◽  
Vol 38 (5) ◽  
pp. 924-935 ◽  
Author(s):  
Christopher J. Fettig ◽  
Robert R. Borys ◽  
Stephen R. McKelvey ◽  
Christopher P. Dabney
Keyword(s):  
Bark Beetle ◽  
Pinus Ponderosa ◽  
Prescribed Fire ◽  
Ponderosa Pine ◽  
Tree Mortality ◽  
Dendroctonus Brevicomis ◽  
Significant Difference ◽  
Pine Beetle ◽  
Low Diversity ◽  
High Diversity

Mechanical thinning and the application of prescribed fire are commonly used tools in the restoration of fire-adapted forest ecosystems. However, few studies have explored their effects on subsequent amounts of bark beetle caused tree mortality in interior ponderosa pine, Pinus ponderosa Dougl. ex P. & C. Laws. var. ponderosa. In this study, we examined bark beetle responses to creation of midseral (low diversity) and late-seral stages (high diversity) and the application of prescribed fire on 12 experimental units ranging in size from 76 to 136 ha. A total of 9500 (5.0% of all trees) Pinus and Abies trees died 2 years after treatment of which 28.8% (2733 trees) was attributed to bark beetle colonization. No significant difference in the mean percentage of trees colonized by bark beetles was found between low diversity and high diversity. The application of prescribed fire resulted in significant increases in bark beetle caused tree mortality (all species) and for western pine beetle, Dendroctonus brevicomis LeConte, mountain pine beetle, Dendroctonus ponderosae Hopkins, Ips spp., and fir engraver, Scolytus ventralis LeConte, individually. Approximately 85.6% (2339 trees) of all bark beetle caused tree mortality occurred on burned split plots. The implications of these and other results to sustainable forest management are discussed.

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