Research And Improvement Of Glowworm Swarm Optimization

Glowworm swarm optimization algorithm(GSO) is a new swarm intelligence optimization algorithm. The algorithm simulates the luminescence properties of glowworm, by comparing the fluorescein value to exchange information, so as to realize the optimization. The algorithm has the advantages of less parameters, simple operation and good stability. With development of the glowworm swarm optimization algorithm theory research, its application is becoming more and more widely, many scholars begin to pay attention to and join the research upsurge.However, theoretical studies and the application of the algorithm has just started, there are still many points to be improved.This paper introduces the theoretical basis, principle and implementation method of GSO in detail, and also analyses the advantages and disadvantages, on this basis, the paper makes improvement on GSO and put forward the two kinds of improved algorithm, improves the optimizing ability. The main research work of this paper includes:(1) First, introduce swarm intelligence optimization algorithm, lists several common optimization algorithm; Then researches and analyzes the GSO, detailed introduces the theoretical knowledge of GSO, including the principle, implementation steps, and current research situation.(2) Puts forward the improvement GSO of adaptive search. Introduce independent random search and step adaptive search mechanism into GSO. Agent of improved GSO can independently search for a better individual in its sensing range, dependence on outstanding individuals will decrease, in addition, by comparing the average distance of neighborhood, step size of individual can be adjusted appropriately in sensing range, thereby reducing the oscillation phenomenon and improving the accuracy of solution. Through the Comparison and analysis of the experimental results, the improved GSO has better optimization ability.(3) Puts forward the PGSO algorithm based on predatory search strategy.Predatory search as a optimization strategy, on the basis of the IGSO, integrated into PSO, two algorithms work together to find the global optimal solution of optimization problem.The PGSO adopts the PSO to improve the global search to find the optimal solution, and then the IGSO searching carefully near the optimal solution to find the global optimal solution. this search strategy is a good method to balance the global search and local search, it improves the overall optimization of the algorithm. The experimental results show that the improved algorithm has good optimization ability.(4) Summarizes the research of this paper and the related work,then puts forward the next research direction.