Hybrid particle swarm optimization and differential evolution for optimal design of water distribution systems

2012 ◽  
Vol 26 (3) ◽  
pp. 582-591 ◽  
Author(s):  
A. Sedki ◽  
D. Ouazar
Keyword(s):  
Particle Swarm Optimization ◽  
Optimal Design ◽  
Differential Evolution ◽  
Distribution Systems ◽  
Water Distribution ◽  
Water Distribution Systems ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Hybrid Particle ◽  
Hybrid Particle Swarm Optimization

scholarly journals An Enhanced Multi-Objective Particle Swarm Optimization in Water Distribution Systems Design

Water ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 1334
Author(s):  
Mohamed R. Torkomany ◽  
Hassan Shokry Hassan ◽  
Amin Shoukry ◽  
Ahmed M. Abdelrazek ◽  
Mohamed Elkholy
Keyword(s):  
Particle Swarm Optimization ◽  
Local Search ◽  
Distribution Systems ◽  
Water Distribution ◽  
Water Distribution Systems ◽  
Particle Swarm ◽  
Large Network ◽  
Swarm Optimization ◽  
Original Algorithm ◽  
Multi Objective

The scarcity of water resources nowadays lays stress on researchers to develop strategies aiming at making the best benefit of the currently available resources. One of these strategies is ensuring that reliable and near-optimum designs of water distribution systems (WDSs) are achieved. Designing WDSs is a discrete combinatorial NP-hard optimization problem, and its complexity increases when more objectives are added. Among the many existing evolutionary algorithms, a new hybrid fast-convergent multi-objective particle swarm optimization (MOPSO) algorithm is developed to increase the convergence and diversity rates of the resulted non-dominated solutions in terms of network capital cost and reliability using a minimized computational budget. Several strategies are introduced to the developed algorithm, which are self-adaptive PSO parameters, regeneration-on-collision, adaptive population size, and using hypervolume quality for selecting repository members. A local search method is also coupled to both the original MOPSO algorithm and the newly developed one. Both algorithms are applied to medium and large benchmark problems. The results of the new algorithm coupled with the local search are superior to that of the original algorithm in terms of different performance metrics in the medium-sized network. In contrast, the new algorithm without the local search performed better in the large network.

scholarly journals Hybrid particle swarm optimization and tabu search for the design of large-scale water distribution networks

RBRH ◽  
2021 ◽  
Vol 26 ◽  
Author(s):  
José Eloim Silva de Macêdo ◽  
José Roberto Gonçalves de Azevedo ◽  
Saulo de Tarso Marques Bezerra
Keyword(s):  
Particle Swarm Optimization ◽  
Tabu Search ◽  
Water Distribution ◽  
Large Scale ◽  
Particle Swarm ◽  
Distribution Networks ◽  
Water Distribution Networks ◽  
Swarm Optimization ◽  
Hybrid Particle ◽  
Hybrid Particle Swarm Optimization

ABSTRACT Water distribution network (WDN) optimization has received special attention from various technicians and researchers, mainly due to its high costs of implementation, operation and maintenance. However, the low computational efficiency of most developed algorithms makes them difficult to apply in large-scale WDN design problems. This article presents a hybrid particle swarm optimization and tabu search (H-PSOTS) algorithm for WDN design. Incorporating tabu search (TS) as a local improvement procedure enables the H-PSOTS algorithm to avoid local optima and show satisfactory performance. Pure particle swarm optimization (PSO) and H-PSOTS algorithms were applied to three benchmark networks proposed in the literature: the Balerma irrigation network, the ZJ network and the Rural network. The hybrid methodology obtained good results when seeking an optimal solution and revealed high computational performance, making it a new option for the optimal design of real water distribution networks.

Parallel Particle Swarm Optimization for Determining Pressure on Water Distribution Systems in R

2018 ◽  
Vol 24 (10) ◽  
pp. 7501-7506 ◽  
Author(s):  
Lala Septem Riza ◽  
Ali Hasan Asyari ◽  
Harsa Wara Prabawa ◽  
Jajang Kusnendar ◽  
Eka Fitrajaya Rahman
Keyword(s):  
Particle Swarm Optimization ◽  
Distribution Systems ◽  
Water Distribution ◽  
Water Distribution Systems ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Parallel Particle Swarm Optimization
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