Dynamic Self-Adaptive Chaotic Particle Swarm Optimization Algorithm in Optimal Control of Public Transit Priority Traffic Signal

Author(s):  
Xueyan Li ◽  
Daming Li
2013 ◽  
Vol 798-799 ◽  
pp. 720-727
Author(s):  
Yu Qiang Chen ◽  
Na Xin Peng

Study the basic theory and process of chaos particle swarm optimization (PSO) algorithm, improve the basic PSO algorithm by introducing the self-adaptive inertia weighting factor method. Construct the mathematical model of basic logistics scheduling to complete the simulation analysis experiments. Experiment results show that self-adaptive chaos particle swarm optimization algorithm is effective and feasible to solve the logistics scheduling model problem.


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