Water Distribution System Computer-Aided Design by Agent Swarm Optimization

Optimal design of water distribution systems (WDS), including the sizing of components, quality control, reliability, renewal and rehabilitation strategies, etc., is a complex problem in water engineering that requires robust methods of optimization. Classical methods of optimization are not well suited for analyzing highly-dimensional, multimodal, non-linear problems, especially given inaccurate, noisy, discrete and complex data. Agent Swarm Optimization (ASO) is a novel paradigm that exploits swarm intelligence and borrows some ideas from multiagent based systems. It is aimed at supporting decisionmaking processes by solving multi-objective optimization problems. ASO offers robustness through a framework where various population-based algorithms co-exist. The ASO framework is described and used to solve the optimal design of WDS. The approach allows engineers to work in parallel with the computational algorithms to force the recruitment of new searching elements, thus contributing to the solution process with expert-based proposals. This work has been developed with the support of the project IDAWAS, DPI2009-11591, of the Spanish Ministry of Education and Science, and ACOMP/2010/146 of the education department of the Generalitat Valenciana. The use of English was revised by John Rawlins. Montalvo Arango, I.; Izquierdo Sebastián, J.; Pérez García, R.; Herrera Fernández, AM. (2014). Water Distribution System Computer-Aided Design by Agent Swarm Optimization. Computer-Aided Civil and Infrastructure Engineering. 29(6):433-448. https://doi.org/10.1111/mice.12062 Adeli, H., & Kumar, S. (1995). Distributed Genetic Algorithm for Structural Optimization. Journal of Aerospace Engineering, 8(3), 156-163. doi:10.1061/(asce)0893-1321(1995)8:3(156) Afshar, M. H., Akbari, M., & Mariño, M. A. (2005). Simultaneous Layout and Size Optimization of Water Distribution Networks: Engineering Approach. Journal of Infrastructure Systems, 11(4), 221-230. doi:10.1061/(asce)1076-0342(2005)11:4(221) Amini, F., Hazaveh, N. K., & Rad, A. A. (2013). Wavelet PSO-Based LQR Algorithm for Optimal Structural Control Using Active Tuned Mass Dampers. Computer-Aided Civil and Infrastructure Engineering, 28(7), 542-557. doi:10.1111/mice.12017 Arumugam, M. S., & Rao, M. V. C. (2008). On the improved performances of the particle swarm optimization algorithms with adaptive parameters, cross-over operators and root mean square (RMS) variants for computing optimal control of a class of hybrid system