Improved Hybrid Frog Leaping Algorithm And Its Application In Crowd Motion Simulation

Shuffled Frog Leaping Algorithm is a kind of imitation biology swarm intelligenceoptimization algorithm. It has been successfully used to solve practical optimization problems.However, due to the time after it has been proposed is short, its current research is not matureand comprehensive enough. Currently, most of the literature on Shuffled Frog LeapingAlgorithm’s theoretical analysis and theoretical research is still in its infancy, it also has a lot ofresearch space worthy of further study.In recent years, the development of virtual reality technology is fast. As an importantresearch direction of virtual reality， crowd motion simulation has broad prospects in industry,entertainment, transportation and other areas, but there are still some challenges. The pathplanning method is an important way to achieve the crowd motion simulation.The main work of this paper is improved the Shuffled Frog Leaping Algorithm, and applyit to the crowd motion simulation based on path planning. The main work and innovation of thispaper is as follows:(1) For Shuffled Frog Leaping Algorithm’s shortcomings of slow convergence and lowconvergence accuracy, we use the advantages of adaptive inertia weight and Artificial BeeColony algorithm to improved algorithm. We use the adaptive inertia weight factor in the localinformation exchange of standard Shuffled Frog Leaping Algorithm, and combine its globalinformation exchange with Artificial Bee Colony algorithm. Eventually propose an improvedShuffled Frog Leaping Algorithm--A2SFLA.Simulation results show that the new algorithmhas improved in convergence speed, capacity optimization and convergence precision than theoriginal algorithm.(2) The Shuffled Frog Leaping Algorithm and its improved algorithm (A2SFLA) is appliedto crowd motion simulation. This paper combined Shuffled Frog Leaping Algorithm andA2SFLA with crowd motion simulation, and simulate in crowd motion simulation system. Thispaper implements the standard motion phenomenon of the crowd, aggregation phenomenon andmulti-exit evacuation phenomenon. The simulation results show that the crowd motionsimulation based on Shuffled Frog Leaping Algorithm and its improved algorithm has a highauthenticity.(3)Depending on the different simulation environment, we propose two hierarchical pathplanning model: hierarchical path planning model based on A*algorithm and hierarchical pathplanning model based on the topology map. The former is suitable for outdoor scenes whereobstacles scattered, while the latter is suitable for indoor scene where is easy to make zoning.Crowd motion simulation results show the effectiveness of the two methods, and exhibitsexcellent simulation performance. Based on these three research content, in research projects have participated, developedseveral modules in “Swarm Intelligence-based Group Simulation System” and” Artificial Life&Swarm Intelligence-based Animation Create System”. The author designed and completedmodules that includes scene establishing module, motion simulation module, the module ofhierarchical path planning based on A*algorithm, the module of hierarchical path planningbased on topology map an algorithms compare module. While the system establishingsimulation scene, it quickly build by parsing the obj scene file. Through experiments we can seethe scene which is rebuild has a good realistic effect.