The topic of multi-objective water distribution systems (WDS) design optimisation using metaheuristics is investigated, comparing numerous modern metaheuristics, including sev- eral multi-objective evolutionary algorithms, an estimation of distribution algorithm and a recent hyperheuristic named AMALGAM (an evolutionary framework for the simultaneous incorporation of multiple metaheuristics), in order to determine which approach is most capa- ble with respect to WDS design optimisation. Novel metaheuristics and variants of existing algorithms are developed, for a total of twenty-three algorithms examined. Testing with re- spect to eight small-to-large-sized WDS benchmarks from the literature reveal that the four top-performing algorithms are mutually non-dominated with respect to the various perfor- mance metrics used. These algorithms are NSGA-II, TAMALGAMJndu , TAMALGAMndu and AMALGAMSndp (the last three being novel variants of AMALGAM). However, when these four algorithms are applied to the design of a very large real-world benchmark, the AMALGAM paradigm outperforms NSGA-II convincingly, with AMALGAMSndp exhibiting the best performance overall.
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