Performance of Heuristic Algorithms in Designing Deformation Monitoring Networks

Abstract

Deformation monitoring is a kind of continuous recording positions (horizontal and vertical coordinates) precisely regardless the deformation pattern and instrument used. In general, a deformation monitoring network can be designed using the trial and error method or analytical methods such as linear programming and nonlinear programming. Recently, a deformation monitoring network may also be designed by heuristic optimization algorithms such as Evolutionary Algorithms (EAs), Particle Swarm Optimization (PSO) and Simulated Annealing (SA). In this paper, heuristic optimization algorithms such as SA and PSO are investigated to design the deformation monitoring networks. The results proved that both SA and PSO are able to determine an optimal design of deformation monitoring and these can used as alternative methods in place of the traditional optimization techniques with high efficiency.