Hybrid Selection Based Multi/Many-Objective Evolutionary Algorithm

Abstract In the last decade, numerous Multi/Many-Objective Evolutionary Algorithms (MOEAs) have been proposed to handle Multi/Many-Objective Problems (MOPs) with challenges such as discontinuous Pareto Front (PF), degenerate PF, etc. MOEAs in the literature can be broadly divided into three categories based on the selection strategy employed such as dominance, decomposition, and indicator-based MOEAs. Each category of MOEAs have their advantages and disadvantages when solving MOPs with diverse characteristics. In this work, we propose a Hybrid Selection based MOEA, referred to as HS-MOEA, which is a simple yet effective hybridization of dominance, decomposition and indicator-based concepts. In other words, we propose a new environmental selection strategy where the Pareto-dominance, reference vectors and an indicator are combined to effectively balance the diversity and convergence properties of MOEA during the evolution. The superior performance of HS-MOEA compared to the state-of-the-art MOEAs is demonstrated through experimental simulations on DTLZ and WFG test suites with up to 10 objectives.

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A Mating Selection Based on Modified Strengthened Dominance Relation for NSGA-III

Mathematics ◽

10.3390/math9222837 ◽

2021 ◽

Vol 9 (22) ◽

pp. 2837

Author(s):

Saykat Dutta ◽

Sri Srinivasa Raju M ◽

Rammohan Mallipeddi ◽

Kedar Nath Das ◽

Dong-Gyu Lee

Keyword(s):

Pareto Front ◽

State Of The Art ◽

Weight Vector ◽

Dominance Relation ◽

Additional Parameter ◽

Pareto Dominance ◽

Environmental Selection ◽

Dominance Relationships ◽

Test Suites ◽

Selection Of

In multi/many-objective evolutionary algorithms (MOEAs), to alleviate the degraded convergence pressure of Pareto dominance with the increase in the number of objectives, numerous modified dominance relationships were proposed. Recently, the strengthened dominance relation (SDR) has been proposed, where the dominance area of a solution is determined by convergence degree and niche size (θ¯). Later, in controlled SDR (CSDR), θ¯ and an additional parameter (k) associated with the convergence degree are dynamically adjusted depending on the iteration count. Depending on the problem characteristics and the distribution of the current population, different situations require different values of k, rendering the linear reduction of k based on the generation count ineffective. This is because a particular value of k is expected to bias the dominance relationship towards a particular region on the Pareto front (PF). In addition, due to the same reason, using SDR or CSDR in the environmental selection cannot preserve the diversity of solutions required to cover the entire PF. Therefore, we propose an MOEA, referred to as NSGA-III*, where (1) a modified SDR (MSDR)-based mating selection with an adaptive ensemble of parameter k would prioritize parents from specific sections of the PF depending on k, and (2) the traditional weight vector and non-dominated sorting-based environmental selection of NSGA-III would protect the solutions corresponding to the entire PF. The performance of NSGA-III* is favourably compared with state-of-the-art MOEAs on DTLZ and WFG test suites with up to 10 objectives.

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Evolutionary Algorithm for Multiobjective Optimization Based on Density Estimation Ranking

Wireless Communications and Mobile Computing ◽

10.1155/2021/4296642 ◽

2021 ◽

Vol 2021 ◽

pp. 1-18

Author(s):

Lin Li ◽

Hengfei Wu ◽

Xiujian Hu ◽

Guanglei Sheng

Keyword(s):

Evolutionary Algorithms ◽

Multiobjective Optimization ◽

Density Estimation ◽

Pareto Front ◽

Selection Criterion ◽

Pareto Dominance ◽

Environmental Selection ◽

Different Shapes ◽

Pareto Fronts ◽

Optimal Candidate

In the past few decades, a number of multiobjective evolutionary algorithms (MOEAs) have been proposed in the continue study. As pointed out in some recent studies, the performance of the most existing MOEAs is not promising when solving different shapes of Pareto fronts. To address this issue, this paper proposes an MOEA based on density estimation ranking. The algorithm includes density estimation ranking to shift the reference solution position, calculating the density of candidate solutions and ranking by the estimated density value, to modify the Pareto dominance relation and for handling complicated Pareto front. The result of this ranking can be used as the second selection criterion for environmental selection, and the optimal candidate individual with distribution and diversity information is selected. Experimental results show that the proposed algorithm can solve various types of Pareto fronts, outperformance several state-of-the-art evolutionary algorithms in multiobjective optimization.

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A Review of Surrogate Assisted Multiobjective Evolutionary Algorithms

Computational Intelligence and Neuroscience ◽

10.1155/2016/9420460 ◽

2016 ◽

Vol 2016 ◽

pp. 1-14 ◽

Cited By ~ 22

Author(s):

Alan Díaz-Manríquez ◽

Gregorio Toscano ◽

Jose Hugo Barron-Zambrano ◽

Edgar Tello-Leal

Keyword(s):

Evolutionary Algorithms ◽

Multiobjective Optimization ◽

Pareto Front ◽

Optimization Problems ◽

State Of The Art ◽

Surrogate Models ◽

Multiobjective Evolutionary Algorithms ◽

Advantages And Disadvantages ◽

Multiobjective Optimization Problems ◽

Computationally Expensive

Multiobjective evolutionary algorithms have incorporated surrogate models in order to reduce the number of required evaluations to approximate the Pareto front of computationally expensive multiobjective optimization problems. Currently, few works have reviewed the state of the art in this topic. However, the existing reviews have focused on classifying the evolutionary multiobjective optimization algorithms with respect to the type of underlying surrogate model. In this paper, we center our focus on classifying multiobjective evolutionary algorithms with respect to their integration with surrogate models. This interaction has led us to classify similar approaches and identify advantages and disadvantages of each class.

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Platelet monitoring for PCI

Hämostaseologie ◽

10.1055/s-0037-1617137 ◽

2009 ◽

Vol 29 (04) ◽

pp. 376-380 ◽

Cited By ~ 9

Author(s):

D. Capodanno ◽

D. J. Angiolillo

Keyword(s):

Interindividual Variability ◽

State Of The Art ◽

Coronary Intervention ◽

Functional Tests ◽

Treatment Regimens ◽

Advantages And Disadvantages ◽

Coronary Syndrome ◽

Combined Use ◽

Increased Risk ◽

Percutaneous Coronary

SummaryDespite the clinical benefit associated with the combined use of aspirin and clopidogrel in patients with acute coronary syndrome or those undergoing percutaneous coronary intervention, a considerable interindividual variability in response to these drugs have been consistently reported. There is a growing interest on applying platelet functional tests with the goal of identifying patients at increased risk of recurrent ischaemic events and potentially tailoring antiplatelet treatment regimens.This manuscript will review the state of the art on the most commonly available platelet functional tests, describing their advantages and disadvantages and exploring their applicability in clinical practice.

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Semi-Supervised PolSAR Image Classification Based on Self-Training and Superpixels

Remote Sensing ◽

10.3390/rs11161933 ◽

2019 ◽

Vol 11 (16) ◽

pp. 1933 ◽

Cited By ~ 5

Author(s):

Yangyang Li ◽

Ruoting Xing ◽

Licheng Jiao ◽

Yanqiao Chen ◽

Yingte Chai ◽

...

Keyword(s):

Image Classification ◽

State Of The Art ◽

Sample Selection ◽

Spatial Relations ◽

Speckle Noise ◽

Classification Performance ◽

Selection Strategy ◽

Training Set ◽

Polarimetric Synthetic Aperture Radar ◽

Unlabeled Sample

Polarimetric synthetic aperture radar (PolSAR) image classification is a recent technology with great practical value in the field of remote sensing. However, due to the time-consuming and labor-intensive data collection, there are few labeled datasets available. Furthermore, most available state-of-the-art classification methods heavily suffer from the speckle noise. To solve these problems, in this paper, a novel semi-supervised algorithm based on self-training and superpixels is proposed. First, the Pauli-RGB image is over-segmented into superpixels to obtain a large number of homogeneous areas. Then, features that can mitigate the effects of the speckle noise are obtained using spatial weighting in the same superpixel. Next, the training set is expanded iteratively utilizing a semi-supervised unlabeled sample selection strategy that elaborately makes use of spatial relations provided by superpixels. In addition, a stacked sparse auto-encoder is self-trained using the expanded training set to obtain classification results. Experiments on two typical PolSAR datasets verified its capability of suppressing the speckle noise and showed excellent classification performance with limited labeled data.

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Utilization of Eco-Friendly Waste Generated Nanomaterials in Water-Based Drilling Fluids; State of the Art Review

Materials ◽

10.3390/ma14154171 ◽

2021 ◽

Vol 14 (15) ◽

pp. 4171

Author(s):

Rabia Ikram ◽

Badrul Mohamed Jan ◽

Akhmal Sidek ◽

George Kenanakis

Keyword(s):

State Of The Art ◽

Superior Performance ◽

Future Research ◽

Drilling Fluids ◽

Drill Cuttings ◽

Environmental Friendly ◽

Water Based ◽

Drilling Operations ◽

Filtration Properties

An important aspect of hydrocarbon drilling is the usage of drilling fluids, which remove drill cuttings and stabilize the wellbore to provide better filtration. To stabilize these properties, several additives are used in drilling fluids that provide satisfactory rheological and filtration properties. However, commonly used additives are environmentally hazardous; when drilling fluids are disposed after drilling operations, they are discarded with the drill cuttings and additives into water sources and causes unwanted pollution. Therefore, these additives should be substituted with additives that are environmental friendly and provide superior performance. In this regard, biodegradable additives are required for future research. This review investigates the role of various bio-wastes as potential additives to be used in water-based drilling fluids. Furthermore, utilization of these waste-derived nanomaterials is summarized for rheology and lubricity tests. Finally, sufficient rheological and filtration examinations were carried out on water-based drilling fluids to evaluate the effect of wastes as additives on the performance of drilling fluids.

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Multiobjective optimization of hard coating parameters designing for damping of the bladed disk

Proceedings of the Institution of Mechanical Engineers Part G Journal of Aerospace Engineering ◽

10.1177/0954410017703149 ◽

2017 ◽

Vol 232 (9) ◽

pp. 1609-1619 ◽

Cited By ~ 1

Author(s):

Yugang Chen ◽

Jingyu Zhai ◽

Qingkai Han

Keyword(s):

Pareto Front ◽

Engineering Application ◽

Front Surface ◽

Model Material ◽

Superior Performance ◽

Hard Coating ◽

Damping Capacity ◽

Nsga Ii ◽

Bladed Disk ◽

Design Variables

In this paper, the damping capacity and the structural influence of the hard coating on the given bladed disk are optimized by the non-dominated sorting genetic algorithm (NSGA-II) coupled with the Kriging surrogate model. Material and geometric parameters of the hard coating are taken as the design variables, and the loss factors, frequency variations and weight gain are considered as the objective functions. Results of the bi-objective optimization are obtained as curved line of Pareto front, and results of the triple-objective optimization are obtained as Pareto front surface with an obvious frontier. The results can give guidance to the designer, which can help to achieve more superior performance of hard coating in engineering application.

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A Systematic Review of Recommender Systems and Their Applications in Cybersecurity

Sensors ◽

10.3390/s21155248 ◽

2021 ◽

Vol 21 (15) ◽

pp. 5248

Author(s):

Aleksandra Pawlicka ◽

Marek Pawlicki ◽

Rafał Kozik ◽

Ryszard S. Choraś

Keyword(s):

Systematic Review ◽

Recommender Systems ◽

Recommender System ◽

State Of The Art ◽

The State ◽

Advantages And Disadvantages ◽

Comprehensive Survey ◽

Security Concerns ◽

Valuable Role

This paper discusses the valuable role recommender systems may play in cybersecurity. First, a comprehensive presentation of recommender system types is presented, as well as their advantages and disadvantages, possible applications and security concerns. Then, the paper collects and presents the state of the art concerning the use of recommender systems in cybersecurity; both the existing solutions and future ideas are presented. The contribution of this paper is two-fold: to date, to the best of our knowledge, there has been no work collecting the applications of recommenders for cybersecurity. Moreover, this paper attempts to complete a comprehensive survey of recommender types, after noticing that other works usually mention two–three types at once and neglect the others.

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Summer Research Placements – State-of-the-Art Science by pre-University Students

MRS Advances ◽

10.1557/adv.2016.128 ◽

2016 ◽

Vol 1 (56) ◽

pp. 3715-3720 ◽

Cited By ~ 1

Author(s):

R. A. Sporea ◽

S. Lygo-Baker

Keyword(s):

University Students ◽

State Of The Art ◽

Group Learning ◽

Student Interaction ◽

Research Tool ◽

Skills Acquisition ◽

Advantages And Disadvantages ◽

Effective Training ◽

Training And Research ◽

Student Training

ABSTRACTSummer research placements are an effective training and research tool. Over three years, our group has hosted nine pre-university students over periods of four to six weeks. Apart from student training and skills acquisition, the placements have produced several peer-reviewed technical publications. Our approach relies on careful pre-planning of activities, frequent student interaction, coupled with independent and group learning. We explore the advantages and disadvantages of this manner of running summer placements.

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New Trends in Asymptotic Approaches: Summation and Interpolation Methods

Applied Mechanics Reviews ◽

10.1115/1.3097289 ◽

2001 ◽

Vol 54 (1) ◽

pp. 69-92 ◽

Cited By ~ 45

Author(s):

Igor V. Andrianov ◽

Jan Awrejcewicz

Keyword(s):

Applied Sciences ◽

Solid Mechanics ◽

State Of The Art ◽

Asymptotic Methods ◽

Perturbation Series ◽

Review Article ◽

Point Of View ◽

Advantages And Disadvantages ◽

New Methods ◽

Local Character

In this review article, we present in some detail new trends in application of asymptotic techniques to mechanical problems. First we consider the various methods which allows for the possibility of extending the perturbation series application space and hence omiting their local character. While applying the asymptotic methods very often the following situation appears: an existence of the asymptotics ε → 0 implies an existence of the asymptotics ε → ∞ (or, in a more general sense, ε → a and ε → b). Therefore, an idea of constructing a single solution valid for a whole interval of parameter ε changes is very attractive. In other words, we discuss a problem of asymptotically equivalent function constructions possessing for ε → a and ε → b a known asymptotic behavior. The defined problems are very important from the point of view of both theoretical and applied sciences. In this work, we review the state-of-the-art, by presenting the existing methods and by pointing out their advantages and disadvantages, as well as the fields of their applications. In addition, some new methods are also proposed. The methods are demonstrated on a wide variety of static and dynamic solid mechanics problems and some others involving fluid mechanics. This review article contains 340 references.

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