The world's population is gradually aging, and the construction of Service Centers for Seniors (SCS) has become an important issue worthy of concern. In this paper, a particle swarm optimization algorithm with random weight and synchronous learning factor (RSPSO) is proposed to optimize the location and compared with three improved PSO algorithms. Experimental results show that RSPSO bears a faster convergence with better improvements on global searching. Furthermore, it can effectively avoid falling into the local optimal solution. The results also demonstrate the superiority of RSPSO over PSO in location optimization of SCS.
Location Optimization of Service Centers for Seniors Based on an Improved Particle Swarm Optimization Algorithm
Smart Innovation, Systems and Technologies
Advances in Smart Vehicular Technology, Transportation, Communication and Applications ; Chapter : 24 ; 249-256
2021-11-30
8 pages
Article/Chapter (Book)
Electronic Resource
English
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