In equation 1, rand determines the movement step sizes of frogs through the x b and x w positions. A memetic metaheuristic called the shuffled frog leaping algorithm sfla has been developed for solving combinatorial optimization problems. An improved shuffled frog leaping algorithm and its. A multi gpu based approach to the 01 knapsack problem using. Pdf an improved shuffled frogleaping algorithm for. The test results show the proposed algorithm gives better results with less computational burden and is fairly consistent in reaching the near optimal solution in recent years. This proposed method is called the maximum entropy based shuffled frog leaping algorithm thresholding mesflot algorithm. Here it is applied to determine optimal discrete pipe sizes. Leaping of the frog is improved by the introduction of cognitive component.

Applied sciences free fulltext shuffled frog leaping algorithm. Shuffled frog leaping algorithm and winddriven optimization technique modified with multilayer perceptron article pdf available in applied sciences 102. An effective hybrid cuckoo search algorithm cs with improved shuffled frog leaping algorithm isfla is put forward for solving 01 knapsack problem. Shuffled frogleaping algorithm and its applications school of. The msfl approach is based on two major modifications on the conventional sfl method. In this paper, we propose an effective heuristic based on the framework of the shuffled frog leaping algorithm sfla for solving the resourceconstrained project scheduling problem rcpsp. We propose using the oppositionbased learning strategy in the shuffled frog leaping. Modified shuffled frog leaping algorithm for solving. The clustering is an important technique for data mining and data analysis.

Improved shuffled frog leaping algorithmbased bp neural. 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. In order to handle large scale problems, this study has used shuffled frog leaping algorithm. Discrete shuffled frog leaping algorithm and its application to 01 knapsack problem. Impa organically made the frog leaping combine with the crossover operator in the pma. To improve the power quality, several methods such.

The sfla is a populationbased cooperative search metaphor inspired by natural memetics. A simple structured matlab implementatio of sfla for global optimization. Greedy algorithms a greedy algorithm is an algorithm that constructs an object x one step at a time, at each step choosing the locally best option. A modified shuffled frogleaping optimization algorithm.

Although the dsfla can lead to an optimal solution, the algorithm might take too long when the problem set increases. Recently, a new metaheuristic algorithm called shuf fled frog leaping algorithm sfla is introduced 11, it aims to model and mimic the behavior of frogs search ing for food laid on stones randomly located in a pond. Abstractthe shuffled frog leaping algorithm sfla, which is a memetic metaheuristic algorithm, is modeled based on the behaviors of the social frogs. A modified shuffled frogleaping optimization algorithm for.

The purpose of the frogs is to find the maksimum food with minimum step. Itisbasedontheevolution of memes carried by individuals and a global exchange of information among the population eusu. Multilevel image threshold selection based on the shuffled. In this paper, we propose this powerful algorithm for solving reactive power dispatch problem. Shuffled frog rleaping algorithm for control of selective and total harmonic distortion, a. In the standard sfl, these step sizes are random num.

Applications to project management evolutionary algorithms, such as shuffled frog leaping, are stochastic search methods. Adaptive grouping cloud model shuffled frog leaping algorithm for. Nov 04, 2015 discrete shuffled frog leaping algorithm and its application to 01 knapsack problem. In some cases, greedy algorithms construct the globally best object by repeatedly choosing the locally best option. Optimization of water distribution network design using the. Data clustering with shuffled leaping frog algorithm sfla. In this paper, a modified shuffled frog leaping msfl algorithm is proposed to overcome drawbacks of standard shuffled frog leaping sfl method. An efficient modified shuffled frog leaping optimization.

In this paper, we proposed an application of shuffled frog leaping algorithm in clustering sflkmeans. An improved population migration algorithm introducing the. Experiments on parameter identification problems confirm a significantly better performance of our proposed. This algorithm has been developed by eusuff and lansey 14. A memetic metaheuristic called the shuffled frogleaping algorithm sfla has been developed for solving combinatorial optimization problems. Use of the improved frogleaping algorithm in data clustering. Shuffled frog leaping algorithm sfla is a metaheuristic for solving discrete optimization problems. As the number of objects in the list increases, the number of frogs that should be processed also increases, making the procedure computationally impractical. 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. Abstract evolutionary algorithms, such as shuffled frog. An intrusion detection method based on shuffle frog leaping.

In this paper, a memetic metaheuristic algorithms called shuffled frogleaping algorithm sfla is used to optimize sampling design variables of composite open channels. The improved algorithm is related to research conducted at the. Pdf shuffled frog leaping algorithm and winddriven. For example, in a problem with decision variables, the frogs are vectors.

By taking three function extreme optimization as example, a contrast is. The proposed idea diversifies search moves of shuffled frog leaping. N2 a memetic metaheuristic called the shuffled frog leaping algorithm sfla has been developed for solving combinatorial optimization problems. The leapfrog methodand other symplectic algorithms for integrating newtons laws of motion peter young dated. A multi gpu based approach to the 01 knapsack problem using the discrete shuffled frog leaping algorithm pranav bhandari, rahul chandrashekhar and peter yoon department of computer science, trinity college, hartford, ct the knapsack problem is a popular combinatorial optimization problem which is of the type np hard. The algorithm uses the probabilistic model of the distribution estimation algorithm to generate new frog population. In this study, an improved algorithm is used to perform clustering. An improved shuffled frogleaping algorithm for solving the. Shuffled frog leaping algorithm sfla file exchange. In the experiments presented in this paper, the exhaustive.

N2 shuffled frog leaping algorithm sfla is a metaheuristic for solving discrete optimization problems. The shuffled frog leaping algorithm sfla easily falls into local. A fuzzyrough based binary shuffled frog leaping algorithm for. Introduction one frequently obtains detailed dynamical information about interacting classical systems from molecular dynamics md simulations, which require integrating newtons equations of motion. Shuffled frogleaping algorithm for control of selective and. Application of shuffled frogleaping algorithm on clustering liacs. Recently, a new metaheuristic algorithm called shuffled frogleaping algorithm sfla is introduced, which aims to model and mimic the behavior of frogs. Shuffled frog leaping algorithm for economic dispatch with. The local search mechanism of frog leaping algorithm and the crossover operator are introduced into the pma in the process of population flow, which can well improve the original search results. Shuffled frog leaping algorithm and winddriven optimization technique. Shuffled frogleaping algorithm for optimal design of open. Pdf application of shuffled frogleaping algorithm on. Shuffled frog leaping algorithm sfla the sfla is a metaheuristic optimisation method that mimics the memetic evolution of a group of frogs when seeking for the location that has that are seeking the maximum amount of available food.

Optimal algorithm of shuffled frog leaping based on immune. Request pdf an efficient modified shuffled frog leaping optimization algorithm in this paper, a modified shuffled frog leaping msfl algorithm is proposed to overcome drawbacks of standard. Sfla algorithm is a new metaheuristic algorithm with efficient mathematical function and global search functionality. A new pulse coupled neural network pcnn for brain medical image fusion empowered by shuffled frog leaping algorithm article pdf available in frontiers in neuroscience march 2019 with 179. Application of shuffled frogleaping algorithm on clustering. The shuffled frogleaping algorithm draws its formulation from two other search techniques. The shuffled frogleaping algorithm draws its formulation from two other search. Application of modified shuffled frog leaping algorithm for. An effective shuffled frogleaping algorithm for resource. An improved shuffled frogleaping algorithm with extremal.

Figure 1 illustrates an example of shear failures for strip footing subsoil and. Application of modified shuffled frog leaping algorithm. This paper reports on a new back propagation bp neural network based on an improved shuffled frog leaping algorithm isfla and its application in bearing fault diagnosis. Pdf optimal placement of distributed generation using. First of all, with the framework of sfla, an improved frog leap operator is designed with the effect of the global optimal information on the frog leaping and information exchange between frog individuals combined with genetic mutation with a. The effectiveness of the proposed approach is demonstrated through ieee30 bus system. It combines the advantages of the geneticbased memetic algorithm ma and the social behaviorbased particle.

An effective shuffled frog leaping algorithm for multiobjective flexible job shop scheduling problems. Physics 115242 the leapfrog methodand other symplectic. Mehrdad mohammadi is a master student in department of industrial engineering, college of engineering, university of tehran, iran. Proposed technique in the proposed approach, shuffled frog leaping algorithm based clustering algorithm sbca is used to find optimal clusterheads in mobile ad hoc networks.

The quay in the container terminal can be configured as either a discrete or continuous quay. It can avoid a local optimum of shuffled frog leaping algorithm. The aim of the partitional clustering is to separate n data objects into k clusters. An objective function is then calculated for each frog and is used as. Genetic and improved shuffled frog leaping algorithms for a 2. To minimize the cost of production or to maximize the efficiency of production. This ensures the faster convergence and global optimal solution.

In order to avoid premature convergence and improve the precision of solution using basic shuffled frog leaping algorithm sfla, based on immune evolutionary particle swarm optimization, a new shuffled frog leaping algorithm was proposed. Its a procedure to make a system or design more effective, especially involving the mathematical techniques. T1 optimization of water distribution network design using the shuffled frog leaping algorithm. We compared sflkmeans with other heuristics algorithm in clustering, such as gak, sa, ts, and aco, by implementing them on several simulations and real datasets. Multi objective combined emission constrained unit commitment. The new metaheuristic is called the shuffled frogleaping algorithm sfla and. Shuffled frog leaping algorithm 32, bacterial foraging 33, artificial bee colony abc 34, firefly algorithm 35, grey wolf optimizer gwo. This paper applies the sflo algorithm to search for the multilevel thresholds using the maximum entropy met criterion. This paper presents an intrusion detection model based on shuffled frog leaping algorithm, the model search speed, high accuracy based on shuffled frog leaping algorithm, using the shuffled frog leaping algorithm generates a set of classification rules from the kdd99 data network audit data collection, quality and the use of objective function shuffled frog leaping algorithm to control the. Oct 17, 2017 optimizationshuffled frog leaping algorithm 2. Our finding shows that the proposed algorithm works better than others.

Count the minimal number of jumps that the small frog must perform to reach its target. Pdf a new pulse coupled neural network pcnn for brain. We propose four new versions of shuffled frog leaping algorithm. An effective hybrid cuckoo search algorithm with improved. Author links open overlay panel junqing li a quanke pan a b c shengxian xie a. An effective shuffled frogleaping algorithm for multi. Request pdf a modified shuffled frog leaping optimization algorithm. The isfla is developed on the basis of a chaotic operator and the convergence factor of particle swarm optimization to overcome the shortcomings of conventional shuffled frog leaping algorithm sfla. An improved shuffled frog leaping algorithm for solving the dynamic and continuous berth allocation problem dcbap article pdf available in applied sciences 20199. The algorithm contains elements of local search and global information exchange. The primary concern of designing a channel is to determine optimum dimensions while minimizing construction costs.

Shuffled frog leaping algorithm based clustering algorithm. Improved shuffled frog leaping algorithm on system reliability analysis. The sfla consists of a set of interacting virtual population of frogs. Genetic and improved shuffled frog leaping algorithms for a 2stage model of a hub covering location network m.

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