As for the search strategy, a modified version of a binary shuffled frog leaping algorithm. In this work, we propose modified versions of shuffled frog leaping algorithm sfla to solve multiple knapsack problems mkp. Recently, shuffled frogleaping algorithm sfla, a memetic. Shuffled frog leaping algorithm sfla file exchange matlab. In this work, a novel multiphase modified shuffled frog leaping algorithm mpmsfla framework is presented to solve the multidepot vehicle routing problem mdvrp more quickly.
Frontiers a new pulse coupled neural network pcnn for. This paper then introduces a new searchacceleration parameter into the formulation of the original shuffled frog leaping algorithm to create a modified form of the algorithm. Developing shuffled frogleaping algorithm sfla method. Article information, pdf download for a shuffled frogleaping. Shuffled frog leaping algorithm sfla is a metaheuristic to handle different largescale optimization problems. The emergence of shuffled frog leaping algorithm sfla offers a promising and effective solution for multiobjective and combinatorial optimization problems.
Multi objective combined emission constrained unit. Application of the shuffled frog leaping algorithm sfla in. The presented algorithm adopts the k means algorithm to execute the clustering analyses for all customers, generates a frog population according to the result of the. Tool path planning of holemaking operations in ejector. In the first modified version called bidirectional differential evolution bde, to generate a new trial point, is used from the bidirectional optimization concept, and in the second modified version called shuffled differential evolution sde, population such as shuffled frog leaping sfl algorithm is divided in to several memeplexes and. The shuffled frogleaping algorithm draws its formulation from two other search. Formulation of shuffled frog leaping algorithm the shuffled frog leaping algorithm is a memetic metaheuristic that is designed to seek a global optimal solution by performing a heuristic search. Mehrdad mohammadi is a master student in department of industrial engineering, college of engineering, university of tehran, iran.
Sfla algorithm free download tutorial videos and source code. A fuzzyrough feature selection based on binary shuffled. Citeseerx document details isaac councill, lee giles, pradeep teregowda. A modified discrete shuffled flog leaping algorithm for. T1 optimization of water distribution network design using the shuffled frog leaping algorithm. Harris hawks optimization for solving optimum load dispatch problem in power system written by mrs. In the shuffled frog leaping algorithm, a population of. In equation 1, rand determines the movement step sizes of frogs through the x b and x w positions. A brief description of the original algorithm is presented along with a pseudocode and flowchart to facilitate its implementation. The purpose of the frogs is to find the maksimum food with minimum step. Generally, one of the major disadvantages of the traditional sfla is the high number of parameters that need to be calibrated for proper operation of the algorithm. A modified shuffled frog leaping algorithm using truncated. N2 shuffled frog leaping algorithm sfla is a metaheuristic for solving discrete optimization problems.
To minimize the cost of production or to maximize the efficiency of production. The efficiency of setting parameters in a modified shuffled frog leaping algorithm applied to optimizing water distribution networks riunet. Pdf this paper discuss a modified shuffled frog leaping algorithm to longterm generation maintenance scheduling to enhance the. Harris hawks optimization for solving optimum load dispatch. This ensures the faster convergence and global optimal solution. An improved shuffled frogleaping algorithm with extremal. Pdf using the modified shuffled frog leaping algorithm. You may receive emails, depending on your notification preferences. Shuffled frog leaping algorithm sfla matlabcentralfileexchange52861shuffledfrogleapingalgorithmsfla, matlab central. Algorithm, various example problems are considered. Sfla is based on the model used by shuffled complex evolution sceua, and incorporated the memetic evolution into it. A modified shuffled frogleaping algorithmbased fuzzy. A new method based on modified shuffled frog leaping algorithm.
The results show that the proposed sfl produces better solutions for two study systems due to extra diversification provided by the algorithm. Shuffled frog leaping algorithm sfla 12, is a metaheuristic algorithm in which a set of frogs or initial solutions cooperate to find the largest source of food. The modified algorithm lisfla is analysed over 15 distinct benchmark test problems and compared with conventional sfla, its recent variant, namely binomial crossover embedded shuffled frog leaping. To show the effectiveness of the proposed algorithm, msfl is tested on economic dispatch. Dastfan, modified shuffled frog leaping algorithm for optimal switch placement in distribution. Two main steps are involved in sfla, namely, local search and global search. Optimal cost reduction in pv system using modified shuffled.
A new frog leaping rule is proposed to improve the local exploration of the sfla, which in turn improves the overall performance of the mslfa. Shuffled frog leaping algorithm sfla file exchange. Multi objective combined emission constrained unit commitment. Issuu is a digital publishing platform that makes it simple to publish magazines, catalogs, newspapers, books, and more online. Distributed generation dg will have a growing role in the future of the power systems. A memetic metaheuristic called the shuffled frog leaping algorithm sfla has been developed for solving combinatorial optimization problems. Shuffled complex evolution sceua is a metaheuristic for global optimization, proposed by duan, gupta and sorooshian, in 1992. Matlab coding process to calculating power load and.
Lin, x, chen, s 2016 a modified shuffled frogleaping algorithmbased fuzzy. Shuffled frog leaping algorithm is a population based random search algorithm inspired by nature memetics. Genetic and improved shuffled frog leaping algorithms for a 2stage model of a hub covering location network m. Shuffled frogleaping algorithm for optimal design of open. A shuffled frogleaping algorithm based mixedsensitivity h. Modified shuffled frog leaping algorithm based 6dof motion. Shuffled frog leaping algorithm sfla is a metaheuristic, or more accurately it is a. The shuffled frog leaping algorithm combines the benefits of the both the geneticbased memetic algorithm ma and the social behaviorbased particle swarm optimization algorithm. A modified shuffled frog leaping algorithm with genetic. Specific optimization process of sfla is illustrated in section 4. Application of modified shuffled frog leaping algorithm for.
The proposed algorithm includes two important operations. The msfl approach is based on an adaptive accelerated position changing of frogs. This paper presents a modified shuffled frog leaping algorithm sfla applied to the design of water distribution networks. The efficiency of setting parameters in a modified. Complex evolution sceua is available in this link, to download. Simple codes for image darkening, lightening and deblurring. Dg reduces line losses and improves system voltage profile. This method has a potential to be a tool for identifying the best location and rating of dg to be installed for reducing line losses in distribution system. An improved shuffled frog leaping algorithm for assembly. This study aims to develop a modified shuffled frogleaping algorithm sfla approach in project scheduling to aid decisionmakers in.
Sfla algorithm free download tutorial videos and source. Application of modified shuffled frog leaping algorithm. A modified and efficient shuffled frog leaping algorithm. Adaptive grouping cloud model shuffled frog leaping algorithm for solving continuous optimization problems. Nov 06, 2015 optimal cost reduction in pv system using modified shuffled frog leaping algorithm dhivyabharathi rajapandian. The msfl approach is based on two major modifications on the conventional sfl method. An improved shuffled frog leaping algorithm for multiload.
Improved shuffled frogleaping algorithm and its application. Distribution automation systems dass involve automatic and remotecontrolled switches. Using the modified shuffled frog leaping algorithm for. Application of shuffled frog leaping algorithm to long term. The clustering is an important technique for data mining and data analysis. The proposed modified shuffled frog leaping algorithm msfla with genetic algorithm ga crossover is designed based on the same framework of shuffled frog leaping algorithm sfla. Optimization of water distribution network design using. Pdf a modified shuffled frog leaping algorithm for. Shuffled frog leaping algorithm sfla is a new memetic, population based, metaheuristic algorithm, has emerged as one of the fast, robust with efficient global search capability. Guide optimal probability and guide suboptimal probability are put forward. The shuffled frog leaping algorithm sfla is a populationbased metaheuristic algorithm which involves repeatedly updating the positions of frogs solutions in subgroup and shuffling frogs among subgroups to find the optimal solution. The sfl algorithm mingles the advantages of the geneticbased memetic algorithms and the social behavior based pso algorithms 9. Sfla involves a set of frogs that cooperate to achieve a unified behavior for the entire system, which produces a robust system that can find highquality solutions to. A modified shuffled frogleaping optimization algorithm for.
Multiphase modified shuffled frog leaping algorithm with. Modified shuffled frog leaping algorithm for optimization of uav flight controller modified shuffled frog leaping algorithm for optimization of uav flight controller huangzhong pu. An efficient modified shuffled frog leaping optimization. The algorithm contains elements of local search and global information exchange. Shuffled frog leaping algorithm is a particle swarm search method based on groups to obtain optimal results. Pdf a modified shuffled frog leaping algorithm for longterm. The difference between the given algorithms is presented as follows. Oct 17, 2017 optimizationshuffled frog leaping algorithm 2. For the evaluation measure, we have employed the fuzzyrough dependency degree frfdd of the lower approximationbased fuzzyrough feature selection lfrfs due to its effectiveness in feature selection. Gagandeep published on 20190628 download full article with reference data and citations. Features fullscreen sharing embed analytics article stories visual stories seo. Using the modified shuffled frog leaping algorithm for optimal sizing and location of distributed generation resources for reliability improvement m.
This paper proposes the modified shuffled frog leaping algorithm sfla to derive the optimal placement of manual and automatic switches in dass. Modified shuffled frog leaping algorithm with genetic. Genetic and improved shuffled frog leaping algorithms for a 2. Modified shuffled frogleaping algorithm based determination. The proposed work is tested with ieee standard 33bus radial distribution system. A simple structured matlab implementatio of sfla for global optimization. An industrial application example of ejector plate of injection mould is considered in this work to demonstrate the proposed approach. First, the population size f, the number of sub populations m, the maximum iterations of local search for each sub population n and the number of frogs in each. A new method based on modified shuffled frog leaping.
Modified shuffled frog leaping algorithm for optimization. Developing shuffled frogleaping algorithm sfla method to. Sfla is a populationbased algorithm that combines the advantages of memetic. A modified shuffled frogleaping optimization algorithm. A modified shuffled frog leaping algorithm for nonconvex. Jan 01, 2016 read a modified shuffled frog leaping algorithm based fuzzy controller for magnetorheological damperbuilding system, international journal of computer applications in technology on deepdyve, the largest online rental service for scholarly research with thousands of academic publications available at your fingertips. A method for calibrating these parameters is presented and applied to the design of three benchmark medium. The sfla is a populationbased cooperative search metaphor inspired by natural memetics.
Abstract in this paper, a modified shuffled frog leaping msfl algorithm is proposed to speed up the convergence of the standard shuffled frog leaping sfl method. This paper proposes an improved shuffled frog leaping algorithm, the algorithm improves the subpopulation frog individual optimization way which is not just the worst individual optimization. The switches play a significant role in system reliability improvement. By using local and global searches simultaneously, sfla is effective for different sorts of optimization problems. In equation 1, rand determines the movement step sizes of frogs through the x b and x w posi tions.
In this study, sfla implemented in matlab was compared to lingo software and other metaheuristic algorithms in designing a channel. Data clustering with shuffled leaping frog algorithm sfla. A modified shuffled frog leaping algorithm msfla is investigated that improves the leaping rule by properly extending the leaping step size and adding a leaping inertia component to account for. Leaping of the frog is improved by the introduction of cognitive component. Image segmentation by optimized kmeans using frog leaping algorithm. Using the modified shuffled frog leaping algorithm for optimal sizing and location of distributed generation resources for reliability improvement. Adaptive grouping cloud model shuffled frog leaping. Thaihoang huynh, a modified shuffled frog leaping algorithm for optimal tuning of multivariable pid controllers, in. Its a procedure to make a system or design more effective, especially involving the mathematical techniques.
Improved shuffled frog leaping algorithm sfla is a memetic algorithm which deals with the behaviour of group of frogs searching for the location that has the maximum amount of available food. Because sce is the abbreviated name of other methods in the science, the ua is added to the abbreviated name of this algorithm, because the creators of this algorithm are members of university of arizona. To apply linear programming, the input output function is to be expressed as a set of linear functions which may lead to loss of accuracy. Designers marketers social media managers publishers. The efficiency of setting parameters in a modified shuffled. In this paper, a modified shuffled frog leaping msfl algorithm is proposed to overcome drawbacks of standard shuffled frog leaping sfl method. Pdf developing shuffled frogleaping algorithm sfla method.