Parallel Hybrid Particle Swarm Optimization and Applications in Geotechnical Engineering
نویسندگان
چکیده
A novel parallel hybrid particle swarm optimization algorithm named hmPSO is presented. The new algorithm combines particle swarm optimization with a local search method which aims to accelerate the rate of convergence. The hybrid global optimization algorithm adjusts its searching space through the local search results. Parallelization is based on the client-server model, which is ideal for asynchronous distributed computations. The server is the center of data exchange, which manages requests and coordinates the timeconsuming computations undertaken by individual clients. A case study in geotechnical engineering demonstrates the effectiveness and efficiency of the proposed algorithm.
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