Non-Dominated Sorting Harmony Search Differential Evolution (NS-HS-DE): A Hybrid Algorithm for Multi-Objective Design of Water Distribution Networks

Abstract

Abstract:We developed a hybrid algorithm for multi-objective design of water distribution networks (WDNs) in the present study. The proposed algorithm combines the global search schemes of differential evolution (DE) with the local search capabilities of harmony search (HS) to enhance the search proficiency of evolutionary algorithms. This method was compared with other multi-objective evolutionary algorithms (MOEAs) including NSGA2, SPEA2, MOEA/D and extended versions of DE and HS combined with non-dominance criteria using several metrics. We tested the compared algorithms on four benchmark WDN design problems with two objective functions, (i) the minimization of cost and (ii) the maximization of resiliency as reliability measure. The results showed that the proposed hybrid method provided better optimal solutions and outperformed the other algorithms. It also exhibited significant improvement over previous MOEAs. The hybrid algorithm generated new optimal solutions for a case study that dominated the best-known Pareto-optimal solutions in the literature.

Multi-objective optimization of water distribution networks: An overview

“…The proposed methodology was tested on a Hanoi network. Yazdi et al (2017) developed a hybrid algorithm for multi-objective design of WDNs. This method combines the global search schemes of DE with the local search capabilities of HS to enhance the search proficiency of EAs.…”

“…However, in WDNs, the optimization process by trial and error methods can present difficulties due to the complexity of these systems such as multiple pumps, valves and reservoirs, head losses, large variations in pressure values, several demand loads, etc. For this reason, innovative linear (Sarbu and Ostafe, 2016), nonlinear (Samani and Naeeni, 1996;Djebedjian et al, 2000;Sarbu and Kalmar, 2002) and heuristic (Simpson et al, 1994;Cunha and Sousa, 2001;Zecchin et al, 2005;Vasan and Simonovic, 2010;Babu and Vijayalakshmi, 2013;Yazdi et al, 2017;El-Ghandour and Elansary, 2018) optimization algorithms are becoming more widely explored in optimization processes of the WDNs. In the solution procedure, each algorithm is linked with a hydraulic analysis solver of WDNs to obtain the optimum solution.…”

Advanced Hydroinformatic Techniques for the Simulation and Analysis of Water Supply and Distribution Systems

“…This issue contains 18 papers which focus on some of the mentioned problems of water distribution system management. The key points are: (i) design of water system [1][2][3][4]; (ii) optimization of network performance assessment [5][6][7][8]; (iii) monitoring and diagnosis of pressure pipe system [9][10][11]; (iv) optimal water quality management [12][13][14]; and (v) modelling and forecasting of water demand [15][16][17][18].…”

“…Secondly, different multiobjective evolutionary algorithms (MOEAs) are compared in [2] on four well-known benchmark networks (i.e., two loop, Hanoi, Fossolo, and Balerma irrigation networks), by taking into account two objective functions: cost minimization and resiliency index maximization. A new hybrid algorithm that combines differential evolution and harmony search algorithm has been proposed for WDS design and compared with five MOEAs (i.e., NSGA2, AMALGAM, Borg, "ε-MOEA", and "ε-NSGA2"): the comparison shows that the new approach outperforms the previous MOEAs.…”

Study on the multi-objective optimization of reliability and operating cost for natural gas pipeline network

“…It can overcome the difficulty in determining the value of algorithm control parameters using the Self-adapting approach [22]. To realize the multi-objective strategy, the DE algorithm can also combine with the Elitist Non-dominated Sorting method, named NS-DE algorithm, which has excellent convergence performance [23,24].…”