Layout and Component Size Optimization of Sewer Network Using Spanning Tree and Modified PSO Algorithm

• Published in: Water resources management Vol. 30; no. 10; pp. 3627 - 3643
• Main Authors: Navin, Praveen K., Mathur, Yogesh P.
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 01.08.2016; Springer Nature B.V
• Subjects: Algorithms; Atmospheric Sciences; Civil Engineering; Design optimization; Earth and Environmental Science; Earth Sciences; Environment; Fluid dynamics; Geotechnical Engineering & Applied Earth Sciences; Graph theory; Heuristic; Hydrogeology; Hydrology/Water Resources; India; Layouts; Networks; Optimization; Optimization algorithms; Sewer systems; Sewers; Size determination; Statistical analysis; Swarm intelligence; system optimization; Trees; India; Sewer network; Spanning tree; Cumulative flow; Optimization; Modified PSO
• ISSN: 0920-4741; 1573-1650
• DOI: 10.1007/s11269-016-1378-7

In the paper, a new method is introduced for optimally solve the problem of the layout and component size determination of sewer network. Simultaneously Layout and component size optimization of sewer network problem consists of many hydraulic constraints which are generally nonlinear and discrete; which creates a challenge even to the modern heuristic search methods. An algorithm generation of a predefined number of spanning trees is introduced to generate a predefined number of sewer layouts of a base sewer network in order of increasing length. These generated layouts are sorted in ascending order of total cumulative flow and sorted layouts are individually optimized for sewer components sizing. It has been found that the optimal sewer layout for total system optimization is one where the total cumulative flow has the minimal value. The modified particle swarm optimization (MPSO) algorithm has been used to optimally determine the component sizes of the selected layouts. The proposed method is applied to the Sudarshanpura sewer network (situated in Jaipur, India) design problem. The results are presented for optimal cost vs cumulative flow of the layouts. Further results of MPSO has been compared with the original PSO algorithm.