Sensor placement optimization of civil engineering structures using GA-SA algorithm
			
	
 
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				1
				Civil Engineering, Henan University of Engineering, China
				 
			 
						
				2
				Art and Design, Henan University of Engineering, China
				 
			 
										
				
				
		
		 
			
			
			
			 
			Submission date: 2024-03-07
			 
		 		
		
			
			 
			Final revision date: 2024-07-01
			 
		 		
		
		
			
			 
			Acceptance date: 2024-07-23
			 
		 		
		
		
			
			 
			Publication date: 2025-09-16
			 
		 			
		 
	
							
					    		
    			 
    			
    				    					Corresponding author
    					    				    				
    					Feng  Li   
    					Civil Engineering, Henan University of Engineering, China
    				
 
    			
				 
    			 
    		 		
			
												 
		
	 
		
 
 
Archives of Civil Engineering 2025;71(3):97-110
		
 
 
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ABSTRACT
Effectively and accurately obtaining the structure and status information of civil engineering by optimizing the configuration of sensors is the basis for the monitoring of civil engineering structures, and it is also the key content for subsequent monitoring and evaluation. To realize the intelligent development of sensor placement optimization, the simulated annealing algorithm is first used to optimize the genetic algorithm, and the sensor placement optimization method of civil engineering structure using genetic simulated annealing algorithm is obtained. The results showed that in the optimization results under the   and   functions, the function values of the genetic simulation annealing algorithm were 0.000045 and -1.031624 in the 125th iteration, respectively, and the algorithm quickly obtained the global optimal solution. In the practical application of civil engineering structures, the genetic simulation annealing algorithm convergence was the best when measurement points were less than 27, and the optimal solution was obtained after 16 iterations. After measurement points exceeded 28, the genetic simulated annealing algorithm obtained excellent optimization results. The above results show that the proposed method can provide targeted optimization solutions for different types of civil engineering structures to achieve the goal of monitoring.