Not availableH.R. Maier, Z. Kapelan, Kasprzyk, J. Kollat, L.S. Matott, M.C. Cunha, G.C. Dandy, M.S. Gibbs, E. Keedwell, A. Marchi, A. Ostfeld, D. Savic, D.P. Solomatine, J.A. Vrugt, A.C. Zecchin, B.S. Minsker, E.J. Barbour, G. Kuczera, F. Pasha, A. Castelletti, M. Giuliani, P.M. Ree

This paper reports the use of many-objective optimization for water distribution system (WDS) design or rehabilitation problems. The term many-objective optimization refers to optimization with four or more objectives. The increase in the number of objectives brings new challenges for both optimization and visualization. This study uses a multiobjective evolutionary algorithm termed the epsilon Nondominated Sorted Genetic Algorithm II (ε-NSGAII) and interactive visual analytics to reveal and explore the tradeoffs for the Anytown network problem. The many-objective formulation focuses on a suite of six objectives, as follows: (1) capital cost, (2) operating cost, (3) hydraulic failure, (4) leakage, (5) water age, and (6) fire-fighting capacity. These six objectives are optimized based on decisions related to pipe sizing, tank siting, tank sizing, and pump scheduling under five different loading conditions. Solving the many-objective formulation reveals complex tradeoffs that would not be revealed i...

This study contributes a many‐objective analysis of the tradeoffs associated with using the portfolio planning approach for managing the urban water supply risks posed by growing population demands and droughts. The analysis focuses on four supply portfolio strategies: (1) portfolios with permanent rights to reservoir inflows, (2) adaptive options contracts added to the permanent rights, (3) rights, options, and leases, and (4) rights, options, and leases subject to a critical reliability constraint used to represent a maximally risk averse case. The portfolio planning strategies were evaluated using a 10 year Monte Carlo simulation of a city in the Lower Rio Grande Valley (LRGV) within Texas. Our solution sets provide the tradeoff surfaces between portfolios' expected values for cost, cost variability, reliability, surplus water, frequency of using leases, and dropped (or unused) transfers of water. Using an additional severe drought scenario, this work shows that leases and options can reduce the potential for critical supply failures when urban supply systems must contend with unexpected and severe extremes in both demand and water scarcity. In summary, this paper contributes a framework that couples interactive visualization and many‐objective optimization to innovate urban water portfolio planning under uncertainty. The many‐objective analysis of the LRGV case study shows that effective water portfolio planning can simultaneously improve the costs, efficiency, and reliability of urban water supply while ensuring adaptability and resiliency to future changes.