Enhanced Local Search in Shuffled Frog Leaping Algorithm

2020 ◽  
pp. 1441-1448
Author(s):  
Tarun K. Sharma ◽  
Jitendra Rajpurohit ◽  
Divya Prakash
Keyword(s):  
Local Search ◽  
Shuffled Frog Leaping Algorithm ◽  
Shuffled Frog Leaping

scholarly journals Enhanced shuffled frog leaping algorithm with improved local exploration and energy-biased load reduction phase for load balancing of gateways in WSNs

2021 ◽  
Vol 11 (1) ◽  
pp. 437-460
Author(s):  
Amol Adamuthe ◽  
Abdulhameed Pathan
Keyword(s):  
Load Balancing ◽  
Convergence Rate ◽  
Local Search ◽  
Heuristic Algorithm ◽  
Information Exchange ◽  
Load Reduction ◽  
Deterministic Approach ◽  
Shuffled Frog Leaping Algorithm ◽  
Shuffled Frog Leaping ◽  
Search Capability

Abstract Wireless sensor networks (WSNs) have grown widely due to their application in various domains, such as surveillance, healthcare, telecommunication, etc. In WSNs, there is a necessity to design energy-efficient algorithms for different purposes. Load balancing of gateways in cluster-based WSNs is necessary to maximize the lifetime of a network. Shuffled frog leaping algorithm (SFLA) is a popular heuristic algorithm that incorporates a deterministic approach. Performance of any heuristic algorithm depends on its exploration and exploitation capability. The main contribution of this article is an enhanced SFLA with improved local search capability. Three strategies are tested to enhance the local search capability of SFLA to improve the load balancing of gateways in WSNs. The first proposed approach is deterministic in which the participation of the global best solution in information exchange is increased. The next two variations reduces the deterministic approach in the local search component of SFLA by introducing probability-based selection of frogs for information exchange. All three strategies improved the success of local search. Second contribution of article is increased lifetime of gateways in WSNs with a novel energy-biased load reduction phase introduced after the information exchange step. The proposed algorithm is tested with 15 datasets of varying areas of deployment, number of sensors and number of gateways. Proposed ESFLA-RW variation shows significant improvement over other variations in terms of successful local explorations, best fitness values, average fitness values and convergence rate for all datasets. Obtained results of proposed ESFLA-RW are significantly better in terms of network energy consumption, load balancing, first gateway die and network life. The proposed variations are tested to check the effect of various algorithm-specific parameters namely frog population size, probability of information exchange and probability of energy-biased load reduction phase. Higher population size and probabilities give better solutions and convergence rate.

scholarly journals A Modified Shuffled Frog Leaping Algorithm for the Topology Optimization of Electromagnet Devices

2020 ◽  
Vol 10 (18) ◽  
pp. 6186
Author(s):  
Wenjia Yang ◽  
Siu Lau Ho ◽  
Weinong Fu
Keyword(s):  
Topology Optimization ◽  
Local Search ◽  
Three Dimensional ◽  
Optimization Method ◽  
Memetic Algorithms ◽  
Local Optimum ◽  
Shuffled Frog Leaping Algorithm ◽  
Electromagnetic Problems ◽  
Electromagnetic Devices ◽  
Shuffled Frog Leaping

The memetic algorithms which employ population information spreading mechanism have shown great potentials in solving complex three-dimensional black-box problems. In this paper, a newly developed memetic meta-heuristic optimization method, known as shuffled frog leaping algorithm (SFLA), is modified and applied to topology optimization of electromagnetic problems. Compared to the conventional SFLA, the proposed algorithm has an extra local search step, which allows it to escape from the local optimum, and hence avoid the problem of premature convergence to continue its search for more accurate results. To validate the performance of the proposed method, it was applied to solving the topology optimization of an interior permanent magnet motor. Two other EAs, namely the conventional SFLA and local-search genetic algorithm, were applied to study the same problem and their performances were compared with that of the proposed algorithm. The results indicate that the proposed algorithm has the best trade-off between the results of objective values and optimization time, and hence is more efficient in topology optimization of electromagnetic devices.

K-Means Clustering Algorithm Method Based on Shuffled Frog Leaping Algorithm

2014 ◽  
Vol 989-994 ◽  
pp. 2245-2249
Author(s):  
Zhe Tang ◽  
Ke Luo
Keyword(s):  
Local Search ◽  
Clustering Algorithm ◽  
Global Search ◽  
Experimental Results ◽  
Shuffled Frog Leaping Algorithm ◽  
The Real ◽  
Searching Strategy ◽  
Shuffled Frog Leaping ◽  
Low Efficiency

Aiming to resolve the problems of the traditional k-means clustering algorithm such as random selecting of initial clustering centers,the low efficiency of clustering,low in the real,this paper proposed a novel k-means clustering algorithm method based on shuffled frog leaping algorithm.This algorithm combined the advantages of k-means algorithm and shunffled forg leaping algorithm.A chaotic local search was introduced to improve the quality of the initial individual,a new searching strategy was presented to update frog position,that increased the optimization ability of algorithm.According to the variation of the frog’s finess variance used k-means algorithm,it has the advantages in the global search ability and convergence speed.The experimental results show that this algorithm has higher accuracy..

Improvement of DV-Hop localization based on shuffled frog leaping algorithm

2011 ◽  
Vol 31 (4) ◽  
pp. 922-924 ◽  
Author(s):  
Yu GE ◽  
Xue-ping WANG ◽  
Jing LIANG
Keyword(s):  
Shuffled Frog Leaping Algorithm ◽  
Shuffled Frog Leaping

scholarly journals A cooperated shuffled frog-leaping algorithm for distributed energy-efficient hybrid flow shop scheduling with fuzzy processing time

2021 ◽  
Author(s):  
Jingcao Cai ◽  
Deming Lei
Keyword(s):  
Energy Efficient ◽  
Flow Shop ◽  
Flow Shop Scheduling ◽  
Hybrid Flow Shop ◽  
Distributed Energy ◽  
Shuffled Frog Leaping Algorithm ◽  
Shop Scheduling ◽  
Fuzzy Processing Time ◽  
Hybrid Flow Shop Scheduling ◽  
Shuffled Frog Leaping

AbstractDistributed hybrid flow shop scheduling problem (DHFSP) has attracted some attention; however, DHFSP with uncertainty and energy-related element is seldom studied. In this paper, distributed energy-efficient hybrid flow shop scheduling problem (DEHFSP) with fuzzy processing time is considered and a cooperated shuffled frog-leaping algorithm (CSFLA) is presented to optimize fuzzy makespan, total agreement index and fuzzy total energy consumption simultaneously. Iterated greedy, variable neighborhood search and global search are designed using problem-related features; memeplex evaluation based on three quality indices is presented, an effective cooperation process between the best memeplex and the worst memeplex is developed according to evaluation results and performed by exchanging search times and search ability, and an adaptive population shuffling is adopted to improve search efficiency. Extensive experiments are conducted and the computational results validate that CSFLA has promising advantages on solving the considered DEHFSP.

Sign in / Sign up

Export Citation Format

Share Document