Finding the shortest path or route is a problem that have been studies by years. Many algorithm have been used to solve this problem one of it is firefly algorithm. Thus this paper done some modified for the light abs...
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ISBN:
(纸本)9781479979523
Finding the shortest path or route is a problem that have been studies by years. Many algorithm have been used to solve this problem one of it is firefly algorithm. Thus this paper done some modified for the light absorption coefficient and used the attractiveness matrix as the guidance to choose the next node till all the nodes is visited only once and return back to the beginning.
Since the past decades, most of the nature inspired optimization algorithms (NIOA) have been developed and become admired due to their effectiveness for resolving a variety of complex problems of dissimilar domain. Fi...
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This paper presents an improvement in stability in a single machine connected to infinite bus power system by designing an optimal fractional order fuzzy PID based power system stabilizer (FOFPID-PSS). The low frequen...
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ISBN:
(纸本)9781538647622
This paper presents an improvement in stability in a single machine connected to infinite bus power system by designing an optimal fractional order fuzzy PID based power system stabilizer (FOFPID-PSS). The low frequency oscillations resulting from load switching are damped out by the designed PSS under different operating conditions. In this paper, a bio-inspired algorithm called firefly algorithm (FA) has been employed for tuning the parameters of the proposed FOFPID-PSS controller. The robustness of the proposed controller is tested for enhancing the transient stability under different operating conditions like step and random variations in load demand. In addition to the graphical results, a comparative analysis of the proposed FOFPID-PSS controller with that of conventional PID-PSS and fuzzy PID-PSS (FPID-PSS) is also presented in terms of the performance indices (PIs) like maximum overshoot, settling time and integral squared error (ISE). The results suggest that the proposed FOFPID-PSS outperforms the FPID-PSS and PID-PSS controllers.
This paper describes the Software Project Scheduling Problem (SPSP) as a combinatorial optimization problem. In this problem raises the need for a process to assign a set of resources to tasks for a project in a given...
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ISBN:
(纸本)9783319336251;9783319336237
This paper describes the Software Project Scheduling Problem (SPSP) as a combinatorial optimization problem. In this problem raises the need for a process to assign a set of resources to tasks for a project in a given time, trying to decrease the duration and cost. The workers are the main resource in the project. We present the design of the resolution model to solve the SPSP using an algorithm of fireflies (firefly algorithm, FA). We illustrate the experimental results in order to demonstrate the viability and soundness of our approach.
The aim of this paper is to propose a model for reliable Distribution centers (DCs) in case of unexpected disruption in DCs. Also, random disruptions between links in a distribution network system. The mixed-integer l...
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ISBN:
(纸本)9781509061068
The aim of this paper is to propose a model for reliable Distribution centers (DCs) in case of unexpected disruption in DCs. Also, random disruptions between links in a distribution network system. The mixed-integer linear programming model (MILP) is formulated that aims to provide reliable DCs in case of random failures. The site-dependent failure probabilities, three investment levels for opening unreliable facility has been considered. The IBM CPLEX 12.6.3 solver has been used to implement recently developed metaheuristic firefly algorithm on the proposed model. Numerical results are presented on basis of random generated examples. The firefly algorithm has outperformed CPLEX on large instances up to 200 customers and 30 DCs.
Orthogonal learning strategy, a proven technique, is combined with hybrid optimization metaheuristic, which is based on firefly algorithm and Particle Swarm Optimization. The hybrid algorithmfirefly Particle Swarm Op...
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ISBN:
(纸本)9783319911892
Orthogonal learning strategy, a proven technique, is combined with hybrid optimization metaheuristic, which is based on firefly algorithm and Particle Swarm Optimization. The hybrid algorithmfirefly Particle Swarm Optimization is then compared, together with canonical firefly algorithm, with the newly created Orthogonal Learning firefly algorithm. Comparisons have been conducted on five selected basic benchmark functions, and the results have been evaluated for statistical significance using Wilcoxon rank-sum test.
The main goal of this paper is to present the performance of two popular algorithms, the first is the firefly algorithm (FA) and the second one is the Grey Wolf Optimizer (GWO) algorithm for complex problems. In this ...
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ISBN:
(纸本)9783030219208;9783030219192
The main goal of this paper is to present the performance of two popular algorithms, the first is the firefly algorithm (FA) and the second one is the Grey Wolf Optimizer (GWO) algorithm for complex problems. In this case the problems that we are presenting are of the CEC 2017 Competition on Constrained Real-Parameter Optimization in order to realize a brief analysis, study and comparison between the FA and GWO algorithms respectively.
firefly algorithm (FA) is an efficient swarm intelligence optimization technique, which has been used to solve many engineering optimization problems. In this paper, we present a new FA (called NFA) variant for demand...
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ISBN:
(纸本)9783319700939;9783319700922
firefly algorithm (FA) is an efficient swarm intelligence optimization technique, which has been used to solve many engineering optimization problems. In this paper, we present a new FA (called NFA) variant for demand estimation of water resources in Nanchang city of China. The performance of the standard FA highly depends on its control parameters. To tackle this issue, a dynamic step factor strategy is proposed. In NFA, the step factor is not fixed and it is dynamically updated during the search process. Three models in different forms (linear, exponential and hybrid) are developed based on the structure of social and economic conditions. Water demand in Nanchang city from 2003 to 2015 is considered as a case study. The data from 2003 to 2012 is used for finding the optimal weights, and the rest data (2013-2015) is for testing the models. Simulation results show that three FA variants can achieve promising performance. Our proposed NFA outperforms the standard FA and memetic FA (MFA), and the prediction accuracy is up to 97.91%.
In the mid-1980s, several metaheuristic methods began to be developed for solving a very large class of computational problems with the aim of obtaining more robust and efficient procedures. Among them, many metaheuri...
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ISBN:
(纸本)9783030912345;9783030912338
In the mid-1980s, several metaheuristic methods began to be developed for solving a very large class of computational problems with the aim of obtaining more robust and efficient procedures. Among them, many metaheuristic methods use bio-inspired intelligent algorithms. In recent years, these methods are becoming increasingly important and they can be used in various subject areas for solving complex problems. firefly algorithm is a nature-inspired optimization algorithm proposed by Yang to solve multimodal optimization problems. In particular, the method is inspired by the nature of fireflies to emit a light signal to attract other individuals of this species. In this work, a numerical study for solving a structural problem using the firefly algorithm as optimization method is conducted. In particular, the implementation of the firefly algorithm in several input files realized in the ANSYS Parametric Design Language has allowed the definition of the optimal stacking sequence and the laminate thickness of a composite gear housing used to enclose the components of a mechanical reducer.
Selecting and extracting feature is a vital step in sentiment analysis. The statistical techniques of feature selection like document frequency thresholding produce sub-optimal feature subset because of the non-polyno...
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ISBN:
(纸本)9789811038747;9789811038730
Selecting and extracting feature is a vital step in sentiment analysis. The statistical techniques of feature selection like document frequency thresholding produce sub-optimal feature subset because of the non-polynomial (NP)-hard character of the problem. Swarm intelligence algorithms are used extensively in optimization problems. Swarm optimization renders feature subset selection by improving the classification accuracy and reducing the computational complexity and feature set size. In this work, we propose firefly algorithm for feature subset selection optimization. SVM classifier is used for the classification task. Four different datasets are used for the classification of which two are in Hindi and two in English. The proposed method is compared with feature selection using genetic algorithm. This method, therefore, is successful in optimizing the feature set and improving the performance of the system in terms of accuracy.
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