A Review and Comparative Study of Firefly Algorithm and its Modified Versions

Firefly algorithm is one of the well-known swarm-based algorithms which gained popularity within a short time and has different applications. It is easy to understand and implement. The existing studies show that it is prone to premature convergence and suggest the relaxation of having constant parameters. To boost the performance of the algorithm, different modifications are done by several researchers. In this chapter, we will review these modifications done on the standard firefly algorithm based on parameter modification, modified search strategy and change the solution space to make the search easy using different probability distributions. The modifications are done for continuous as well as non-continuous problems. Different studies including hybridization of firefly algorithm with other algorithms, extended firefly algorithm for multiobjective as well as multilevel optimization problems, for dynamic problems, constraint handling and convergence study will also be briefly reviewed. A simulation-based comparison will also be provided to analyse the performance of the standard as well as the modified versions of the algorithm

Modeling Advertising Practices for Product Involvement and Consumer Impulsivity in Branded Apparel: A Case Study of Indian Consumers

The exponential growth of advertising in enhancing consumer impulsivity has drawn the interest of many researchers to explore the various dimensions of advertising and its effective modeling. The branded apparel product market has grown significantly, a large number of competitors have entered into the market with variant quality, and there are a number of attractive advertising practices. The main aim of this study was to analyze the advertising practices and their relationship with consumer product involvement and the impulsive buying behavior of consumers in branded apparel in India. In a survey of 445 Indian customers, the study indicated that advertising practices significantly affect consumer involvement in branded apparel products and enhance their impulsivity toward products. The study also indicated that the level of consumer involvement in the branded apparel product significantly mediates the relationship between advertising practices and consumer impulsive buying behavior. Effective advertising practices will help companies to enhance consumer involvement that will enable branded apparel companies in enhancing consumer impulsiveness toward products. Some of the managerial implications, limitations, and scope of future research are also presented in the study

Using Artificial Neural Network with Prey Predator Algorithm for Prediction of the COVID-19: The Case of Brazil and Mexico

The spread of the COVID-19 epidemic worldwide has led to investigations in various aspects, including the estimation of expected cases. As it helps in identifying the need to deal with cases caused by the pandemic. In this study, we have used artificial neural networks (ANNs) to predict the number of cases of COVID-19 in Brazil and Mexico in the upcoming days. Prey predator algorithm (PPA), as a type of metaheuristic algorithm, is used to train the models. The proposed ANN models’ performance has been analyzed by the root mean squared error (RMSE) function and correlation coefficient (R). It is demonstrated that the ANN models have the highest performance in predicting the number of infections (active cases), recoveries, and deaths in Brazil and Mexico. The simulation results of the ANN models show very well predicted values. Percentages of the ANN’s prediction errors with metaheuristic algorithms are significantly lower than traditional monolithic neural networks. The study shows the expected numbers of infections, recoveries, and deaths that Brazil and Mexico will reach daily at the beginning of 2021

Influence of Electronic Word of Mouth (eWOM) and Relationship Marketing on Brand Resonance: A Mediation Analysis

This study investigates how electronic work of mouth (eWOM) mediates the relationship between marketing relations and brand resonance. Based on the information obtained from 473 customers using an online questionnaire, this study analyses the relationship between eWOM, relationship marketing practices and the brand resonance of lifestyle products in an Indian context. The results from the multiple regression analysis indicate that the proposed hypotheses are valid, that relationship marketing significantly affects brand resonance, and that eWOM significantly mediates the relationship between the relationship marketing and brand resonance of branded apparel. The findings suggest that personalized attention and tangible rewards are effective relationship marketing strategies, and that these relationship-marketing practices—in association with eWOM—build up the strong brand resonance of branded apparel. The present study recommends that marketers should place emphasis on effective online and offline relationship marketing strategies, and should design appropriate eWOM strategies to enhance brand loyalty, brand attachment, brand community and brand engagement. Some of the managerial implications and the future scope of study based on the empirical findings are also highlighted in the present research work

Gender Sensitivity in Accessing Healthcare Services: Evidence from Saudi Arabia

Good health and reduced inequality are factors of sustainable development. Healthcare systems are considered on68e of the most important activities of the creative economy that arise from research and development activities. Therefore, facilitating access to healthcare is one of the most important challenges guiding the development of the healthcare systems. Access is a complex concept and requires at least four aspects of evaluation. These include whether services are available, whether there is an adequate supply of services, whether people could obtain healthcare, and finally, evaluating whether a population may have access to services. Most countries are working hard to explore the means of providing better healthcare services to their population, especially in the pandemic age of crisis. The Kingdom of Saudi Arabia (KSA) is one such country that is continuously trying to enhance healthcare access to its citizens by adopting different means and policy interventions. The primary objective of this study is to assess whether gender differences exist with unmet healthcare needs among the citizens of the KSA. In this study, we examined the factors affecting the healthcare system in the Kingdom through access to and use of primary healthcare centres in urban and rural areas and whether there is a gender gap in access to healthcare services. In addition, we have tried to explore the current challenges faced by the healthcare system and key points about immediate measures to overcome the crisis in this sector. A well-structured questionnaire was designed covering different dimensions of the study objectives. The population of the study includes both male and female citizens of Makkah city of the KSA. In a survey of 529 respondents, it was found that people’s access to the healthcare service system in the area is good. Test statistics confirm the significant difference in healthcare access across the gender categories of respondents. The availability of services, as well as the barriers to access, must be evaluated in the context of varied groups in society’s differing perspectives, health requirements, and material and cultural surroundings. Some theoretical and managerial implications, limitations, and scope of future research are also presented in the study

Prediction of thermal conductivity of polyvinylpyrrolidone (PVP) electrospun nanocomposite fibers using artificial neural network and prey-predator algorithm.

In this study, multilayer perception neural network (MLPNN) was employed to predict thermal conductivity of PVP electrospun nanocomposite fibers with multiwalled carbon nanotubes (MWCNTs) and Nickel Zinc ferrites [(Ni0.6Zn0.4) Fe2O4]. This is the second attempt on the application of MLPNN with prey predator algorithm for the prediction of thermal conductivity of PVP electrospun nanocomposite fibers. The prey predator algorithm was used to train the neural networks to find the best models. The best models have the minimal of sum squared error between the experimental testing data and the corresponding models results. The minimal error was found to be 0.0028 for MWCNTs model and 0.00199 for Ni-Zn ferrites model. The predicted artificial neural networks (ANNs) responses were analyzed statistically using z-test, correlation coefficient, and the error functions for both inclusions. The predicted ANN responses for PVP electrospun nanocomposite fibers were compared with the experimental data and were found in good agreement

Modeling and Optimization of Gaseous Thermal Slip Flow in Rectangular Microducts Using a Particle Swarm Optimization Algorithm

In this study, pressure-driven flow in the slip regime is investigated in rectangular microducts. In this regime, the Knudsen number lies between 0.001 and 0.1. The duct aspect ratio is taken as 0 ≤ ε ≤ 1 . Rarefaction effects are introduced through the boundary conditions. The dimensionless governing equations are solved numerically using MAPLE and MATLAB is used for artificial neural network modeling. Using a MAPLE numerical solution, the shear stress and heat transfer rate are obtained. The numerical solution can be validated for the special cases when there is no slip (continuum flow), ε = 0 (parallel plates) and ε = 1 (square microducts). An artificial neural network is used to develop separate models for the shear stress and heat transfer rate. Both physical quantities are optimized using a particle swarm optimization algorithm. Using these results, the optimum values of both physical quantities are obtained in the slip regime. It is shown that the optimal values ensue for the square microducts at the beginning of the slip regime

Experimental arrangement of thermal conductivity measurement.

<p>Experimental arrangement of thermal conductivity measurement.</p

Experimental values of PVP polymer data Wt. % (NiZn Ferrites) with the corresponding predicted model values.

<p>Experimental values of PVP polymer data Wt. % (NiZn Ferrites) with the corresponding predicted model values.</p

Modification of the Optimal Auxiliary Function Method for Solving Fractional Order KdV Equations

In this study, a new modification of the newly developed semi-analytical method, optimal auxiliary function method (OAFM) is used for fractional-order KdVs equations. This method is called the fractional optimal auxiliary function method (FOAFM). The time fractional derivatives are treated with Caputo sense. A rapidly convergent series solution is obtained from the FOAFM and is validated by comparing with other results. The analysis proves that our method is simplified and applicable, contains less computational work, and has fast convergence. The beauty of this method is that there is no need to assume a small parameter such as in the perturbation method. The effectiveness and accuracy of the method is proven by numerical and graphical results