The Research Based On Shuffled Frog-leaping Algorithm

A memetic meta-heuristic called the shuffled frog-leaping algorithm(SFLA) has been introduced by Eusuff and Lansey in 2000.The SFLA contains elements of powful local search and strong global information exchange,and simple in concept,few in parameters.The algorithm has been tested on several discrete and continuous function optimizations.The effectiveness and suitablility of this algorithm have also been demonstrated by applying it to a groundwater distribution system design problem, non-linear function optimization,TSP.Compared with other meta-heuristic algorithm, there are few research results in SFLA,so there are many fields that need research such as the demonstration of diversity,how to improve the effectiveness of result space, parameter selection,the local search method.Firstly,it has introduced the background knowledge and the research results of foreign and domestic country and the foundation of SFLA.It has discussed the principles and the effects of the parameters section about the population and the after-iteration.It has provided a better understanding of the parameters' impacts.Secondly,due to the drawbacks of SFLA,an improved shuffled frog-leaping algorithm(Im-SFLA) was proposed.It has presented the new step formula and the flowdraw.The acceleration operation and mutation operation will be added into the improved SFLA that speed up the local search and avoid the common defect of premature convergence,and improve the ability of exploration and search.The performance of Im-SFLA was demonstrated through functions and compared with SFLA and PSO.Thirdly,the improved SFLA has been applied to multi-objective optimization problem and the effectiveness of Im-SFLA was presented by the test functions compared with SFLA.Finally,the work of this dissearttion is summarized and the prospectiveof future research is discussed.