Robust multi‐objective optimization for water distribution system design using a meta‐metaheuristic

Abstract

The design of an urban water distribution system (WDS) is a challenging problem involving multiple objectives. The goal of robust multi-objective optimization for WDS design is to find the set of solutions which embodies an acceptable trade-off between system cost and reliability, so that the ideal solution may be selected for a given budget. In addition to satisfying consumer needs, a system must be built to accommodate multiple demand loading conditions, withstand component failures and allow surplus capacity for growth. In a developmental setting, WDS robustness becomes even more crucial, owing to the limited availability of resources, especially for maintenance. Recent optimization studies have achieved success using multi-objective evolutionary algorithms, such as the Non-dominated Sorting Genetic Algorithm II (NSGA-II). However, the multi-objective design of a large WDS within a reasonable timeframe remains a formidable problem, owing to the extremely high computational complexity of the problem. In this paper, a meta-algorithm called AMALGAM is applied for the first time to WDS design. AMALGAM uses multiple metaheuristics simultaneously in an attempt to improve optimization performance. Additionally, a Jumping-gene Genetic Algorithm (NSGA-II-JG) is also applied for the first time to WDS design. These two algorithms were tested against some other metaheuristics (including NSGA-II and a new greedy algorithm) with respect to a number of benchmark systems documented in the literature, and AMALGAM demonstrated the best performance overall, while NSGA-II-JG fared worse than the ordinary NSGA-II. Large cost savings and reliability improvements are demonstrated for a real WDS developmental case study in South Africa.

Comparing Low and High-Level Hybrid Algorithms on the Two-Objective Optimal Design of Water Distribution Systems

“…In addition, AMALGAM provides a general template which is flexible and extensible, and can easily accommodate any other population-based algorithm (Raad et al 2009;2011).…”

“…In order to overcome their limits and then to obtain a better numerical performance, hybrid algorithms that combine different components and strategies have then been proposed in the scientific literature of water supply systems (Jourdan et al, 2004;Olsson et al, 2009;Raad et al 2009;Raad et al 2011;2012;2013a;Wang et al, in press). …”

“…Although the PFs obtained by these LLHAs suffer from the problem of satisfactory diversity, they offered significantly better solutions than NSGA-II in terms of convergence for the case of large systems. Raad et al (2009) addressed three benchmark problems as well as a real case in South Africa using a HLHA for the first time. This HLHA was based on the framework of To be cited as: .…”

A review of the Tom Rozwadowski medal

“…In this case (Raad et al 2009) the goal was to find the set of solutions which embodies an acceptable trade-off between system cost and reliability, so that the ideal solution may be selected for a given budget. A metaheuristic algorithm is applied to a WDS design.…”

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

“…The results showed the proposed algorithm has better performance for solving complex problems with respect to a few other MOEAs. Raad et al [20] compared various hybrid optimization algorithms (AMALGAM, NSGA2, NSGA2-JG) for optimal design of WDNs. AMALGAM showed the best results.…”