Swarm and Evolutionary Computation

Items from 1 to 11 out of 11 results

article

hGRGA: A scalable genetic algorithm using homologous gene schema replacement

Sumaiya Iqbal, Md Tamjidul Hoque

Swarm and Evolutionary Computation > 2017 > 34 > C > 33-49

In this article, we propose a new evolutionary algorithm, referred as homologous Gene Replacement Genetic Algorithm (hGRGA) that includes a novel and generic operator called homologous Gene Replacement (hGR). The hGR operator improves the chromosomes in gene level to promote their overall functionality. The hGRGA effectively encodes the key idea of the natural evolutionary process that locates and...

article

Multi-objective two-level swarm intelligence approach for multiple RNA sequence-structure alignment

Soniya Lalwani, Rajesh Kumar, Kusum Deep

Swarm and Evolutionary Computation > 2017 > 34 > C > 130-144

This paper proposes a novel two-level particle swarm optimization algorithm for multi-objective optimization (MO-TLPSO) employed to a challenging problem of bioinformatics i.e. RNA sequence-structure alignment. Level one of the proposed approach optimizes the dimension of each swarm which is sequence length for the addressed problem, whereas level two optimizes the particle positions and then evaluates...

article

Inside Front Cover: Editorial board

Swarm and Evolutionary Computation > 2017 > 34 > C > IFC

article

On the use of two reference points in decomposition based multiobjective evolutionary algorithms

Zhenkun Wang, Qingfu Zhang, Hui Li, Hisao Ishibuchi, more

Swarm and Evolutionary Computation > 2017 > 34 > C > 89-102

Decomposition based multiobjective evolutionary algorithms approximate the Pareto front of a multiobjective optimization problem by optimizing a set of subproblems in a collaborative manner. Often, each subproblem is associated with a direction vector and a reference point. The settings of these parameters have a very critical impact on convergence and diversity of the algorithm. Some work has been...

article

Success rates analysis of three hybrid algorithms on SAT instances

Xinsheng Lai, Yuren Zhou

Swarm and Evolutionary Computation > 2017 > 34 > C > 119-129

In recent years, combining different individual heuristics to construct hybrid algorithms seems to be a promising way for designing more powerful algorithms. We are interested in when a certain termination criterion is met, whether the success (referring to finding a globally optimal solution) rate of a hybrid algorithm can be better than that of the individual algorithms on which the hybrid algorithm...

article

Particle swarm clustering fitness evaluation with computational centroids

Jenni Raitoharju, Kaveh Samiee, Serkan Kiranyaz, Moncef Gabbouj

Swarm and Evolutionary Computation > 2017 > 34 > C > 103-118

In this paper, we propose a new way to carry out fitness evaluation in dynamic Particle Swarm Clustering (PSC) with centroid-based encoding. Generally, the PSC fitness function is selected among the clustering validity indices and most of them directly depend on the cluster centroids. In the traditional fitness evaluation approach, the cluster centroids are replaced by the centroids proposed by a...

article

A fast hypervolume driven selection mechanism for many-objective optimisation problems

Shahin Rostami, Ferrante Neri

Swarm and Evolutionary Computation > 2017 > 34 > C > 50-67

Solutions to real-world problems often require the simultaneous optimisation of multiple conflicting objectives. In the presence of four or more objectives, the problem is referred to as a “many-objective optimisation problem”. A problem of this category introduces many challenges, one of which is the effective and efficient selection of optimal solutions.The hypervolume indicator (or s-metric), i...

article

A novel teaching-learning based optimization approach for design of broad-band anti-reflection coatings

Sanjaykumar J. Patel, Aditi Toshniwal, Vipul Kheraj

Swarm and Evolutionary Computation > 2017 > 34 > C > 68-74

The design of thin-film multilayered anti-reflection (AR) coating is quite an intricate task due to highly nonlinear and complex dimensional search space, which includes many local minima. In this paper, a novel teaching-learning based optimization (TLBO) approach is employed to design ultra-low reflective coating over a broad wavelength-band using multilayer thin-film structures for optoelectronic...

article

Time series analysis and short-term forecasting of solar irradiation, a new hybrid approach

N. Bigdeli, M. Salehi Borujeni, K. Afshar

Swarm and Evolutionary Computation > 2017 > 34 > C > 75-88

In this paper, nonlinear time series analysis and short-term prediction of solar irradiation were considered, simultaneously. The proposed methodology is to employ time series analysis methods as well as swarm and evolutionary algorithms in conjunction with well-known regression, fuzzy and neural network model structures to develop a simple but efficient and applicable model for solar irradiation...

article

A production inventory model with price discounted fuzzy demand using an interval compared hybrid algorithm

Anindita Kundu, Partha Guchhait, Prasenjit Pramanik, Manas Kumar Maiti, more

Swarm and Evolutionary Computation > 2017 > 34 > C > 1-17

An economic production quantity (EPQ) model in an imprecise environment is proposed, where the production rate, planning horizon and demand coefficients are fuzzy in nature. At the beginning of each cycle a price discount is offered for a period to boost the demand. During this period, demand increases with time depending upon the amount of discount. Here, demand also depends on the unit selling price...

article

Rocchio algorithm-based particle initialization mechanism for effective PSO classification of high dimensional data

Anwar Ali Yahya, Addin Osman, Mohammad Said El-Bashir

Swarm and Evolutionary Computation > 2017 > 34 > C > 18-32

In recent years, there has been a growing interest in applying Particle Swarm Optimization (PSO) to data classification. Nonetheless, due to the curse of dimensionality, the effectiveness of the PSO applied to high dimensional data classification becomes questionable. This paper proposes a novel specialized PSO initialization mechanism, developed specifically for PSO applications to high dimensional...

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34
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2017

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Keywords

PARTICLE SWARM OPTIMIZATION (3)
ANFIS (1)
ANTI-REFLECTION COATING (1)
BENCHMARK EQUATIONS (1)
BLOOM'S TAXONOMY (1)
CLEAR SKY IRRADIATION (1)
CONFLICTING OBJECTIVES (1)
DECOMPOSITION (1)
EDUCATIONAL DATA MINING (1)
EPQ MODEL (1)
EVOLUTIONARY OPTIMISATION (1)
FAST CONVERGENCE (1)
FLOWER POLLINATION ALGORITHM (FPA) (1)
FUZZY DIFFERENTIAL EQUATION (1)
FUZZY RIEMANN INTEGRATION (1)
GENETIC ALGORITHMS (1)
HEURISTIC ALGORITHMS (1)
HIGH DIMENSIONAL DATA (1)
HOMOLOGOUS GENE REPLACEMENT (1)
HYBRID ALGORITHM (1)
HYPERVOLUME INDICATOR (1)
MANY-OBJECTIVE OPTIMISATION (1)
MARKOV CHAIN (1)
MINIMUM FREE ENERGY (1)
MULTI-OBJECTIVE OPTIMISATION (1)
MULTI-OBJECTIVE OPTIMIZATION (1)
MULTIOBJECTIVE OPTIMIZATION (1)
MULTIPLE SEQUENCE ALIGNMENT (1)
MULTIVARIATE REGRESSION MODEL (1)
NON-DOMINATED SOLUTIONS (1)
OPTIMIZATION (1)
OPTIMIZATION ALGORITHMS (1)
PARETO OPTIMAL SOLUTION (1)
PARTICLE SWARM CLASSIFICATION (1)
PARTICLE SWARM-GENETIC ALGORITHM (1)
PATTERN CLUSTERING (1)
PRICE DISCOUNTED FUZZY DEMAND (1)
RECURRENCE PLOT (1)
REFERENCE POINTS (1)
RNA SECONDARY STRUCTURE (1)
SATISFIABILITY (1)
SCALABLE (1)
SELECTION MECHANISM (1)
SOLAR IRRADIATION CORRELATION ANALYSIS (1)
SUCCESS RATE (1)
SWARM INTELLIGENCE (1)
TEACHING-LEARNING BASED OPTIMIZATION (1)
TEST INSTANCE (1)
THIN-FILMS AND LABVIEW (1)
TIME COMPLEXITY (1)
VALIDITY INDEX (1)
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Swarm and Evolutionary Computation

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