3 - Particle Swarm Optimization in Civil Infrastructure Systems: State-of-the-Art Review

Abstract

Particle swarm optimization (PSO), a metaheuristic search algorithm inspired by flocks of birds and schools of fish, has been highly successful in solving a wide range of difficult optimization problems. There has been an exponential growth in the number of publications reporting on the applications of PSO in diverse scientific fields including signal processing, graphics, robotics, and so on. As an optimization tool, PSO has seen similar success in the civil engineering arena, where it has been used in solving shape and size optimization problems in structural design, structural condition assessment and health monitoring, structural material characterization and modeling, transportation network design, traffic flow forecasting, traffic control, traffic accident forecasting, river stage prediction, design optimization of water/wastewater distribution networks, solving reservoir operation problems, parameter estimation/calibration of hydrological models, construction planning, scheduling and management, construction litigation, construction cost estimation and prediction, inverse parameter identification and geotechnical model calibration, slope stability analysis, pavement engineering, and so on. This chapter presents a state-of-the-art review of PSO applications in civil infrastructure systems reported mainly in archival journals and conference proceedings from 1995 (the year of PSO’s inception) until now.