Multi-objective Optimization for Monitoring Sensor Placement in Water Distribution Systems

Pump management and reservoir management have many similarities, and therefore, should ideally be analyzed in an integrated way to plan effectively the daily operation of water distribution systems. Historically, these two management activities have been evolved as separate tasks in energy-efficiency (i.e., energy optimization) studies and are often carried out in an isolated way. The latter being most often associated directly with the concepts of multimodal and multi-objective optimization problems, whereas the former is usually considered as a single optimization problem to be solved. When some single optimization problems appear at part of the solution tied to a local (i.e., regional) search-space (i.e., objective space), this artificial integration (i.e., multi-modal and multi-objective optimization) can always obtain optimal solutions. Similarly when system constraints and load conditions are considered, a set of feasible and innovative optimal solutions can be obtained in order to continue the enhancement of energy consumption that turns into a significant reduction in the overall operational cost (i.e., a potential of 6.24% cost savings) without affecting the level of services provided to the clients in a safe and protected manner.

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An efficient decomposition and dual-stage multi-objective optimization method for water distribution systems with multiple supply sources

Environmental Modelling & Software ◽

10.1016/j.envsoft.2014.01.028 ◽

2014 ◽

Vol 55 ◽

pp. 143-155 ◽

Cited By ~ 38

Author(s):

Feifei Zheng ◽

Aaron Zecchin

Keyword(s):

Distribution Systems ◽

Water Distribution ◽

Water Distribution Systems ◽

Optimization Method ◽

Multi Objective Optimization ◽

Multi Objective ◽

Dual Stage

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

Water ◽

10.3390/w13101334 ◽

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.

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