Yetkin, M.Inal, C.2020-03-262020-03-262015978-3-319-10828-5; 978-3-319-10827-80939-9585https://dx.doi.org/10.1007/978-3-319-10828-5_5https://hdl.handle.net/20.500.12395/323961st IAG International Workshop on the Quality of Geodetic Observation and Monitoring Systems (QuGOMS) -- APR 13-15, 2011 -- Tech Univ Munchen, Int Grad Sch Sci & Engn, Munich, GERMANYGeodetic networks are very important tools that can be used to monitor crustal movements or the deformation of structures. However, a geodetic network must be designed to sufficiently meet some network quality requirements such as accuracy, reliability, sensitivity and economy. This is the subject of geodetic network optimization. Traditional methods have been used for solving geodetic optimization problems. On the other hand, some evolutionary algorithms such as the particle swarm optimization algorithm have been started to be recently used. These methods are inspired by optimization and adaptation processes that are encountered in the nature. They are iterative procedures for quickly and efficiently solving complex optimization problems. They may provide global optimum solution or at least near-optimum solutions to problems. In this paper, the use of the shuffled frog-leaping algorithm for the optimal design of a deformation monitoring network is studied. The aim is to design and optimize a geodetic network in terms of high reliability.en10.1007/978-3-319-10828-5_5info:eu-repo/semantics/closedAccessFirst-order designGeodetic network optimizationNature-inspired optimization algorithmsNetwork reliabilityStochastic search methodsConference Object1402731N/AWOS:000357499300005N/A