Bibliographic Details
| Title: |
Hybrid Evolutionary‐Exact Optimization Method for the Bi‐Objective Design‐For‐Control of Water Distribution Networks. |
| Authors: |
Ulusoy, Aly‐Joy, Stoianov, Ivan |
| Source: |
Water Resources Research; Feb2026, Vol. 62 Issue 2, p1-24, 24p |
| Subject Terms: |
Evolutionary algorithms, Nonlinear programming, Heuristic, Municipal water supply, Multi-objective optimization, Mathematical optimization, Pressure regulators |
| Abstract: |
This work considers the design‐for‐control of water distribution networks (WDN) for the joint optimization of performance and cost‐related objectives. In particular, we focus on the problem of optimizing the placement (design) and settings (control) of pressure reducing valves to minimize leakage at minimum cost. We present an integrative hybrid method combining the complementary advantages of deterministic and evolutionary algorithms (EA) to efficiently approximate the Pareto front of the resulting non‐convex bi‐objective mixed‐integer non‐linear program. Design decisions are fixed by an outer multi‐objective EA, while a non‐linear programming solver is called during the fitness evaluation stage to compute continuous control settings. The algorithm is applied to case study and operational networks and evaluated against alternative heuristic methods based on computational performance and quality of the solutions returned. Our results show that the proposed method converges faster and more consistently than existing approaches, producing better trade‐offs between cost and leakage reduction. In particular, the Pareto front approximations computed using the proposed integrative hybrid method are characterized by a more marked knee (i.e., more efficient trade‐offs), while the achieved computational improvements facilitate the integration of expert feedback into the design‐for‐control of WDNs during offline planning. Plain Language Summary: This manuscript addresses the optimal placement of valves and adjustment of their settings in water distribution networks to reduce pressure (and, as a result, leakage) at minimum cost. To solve this problem, we develop a hybrid method combining two complementary types of algorithms: an evolutionary algorithm is used to make design decisions, while a non‐linear programming solver fine‐tunes the control settings. We apply the proposed approach to case studies and real‐world water distribution networks, and compare its performance to alternative methods. The results show our method is faster and more reliable, providing better solutions with more efficient trade‐offs. This improvement also makes it easier to incorporate operator feedback into the design process. Key Points: Jointly optimizing the performance and design cost of a water network results in a non‐convex bi‐objective mixed‐integer non‐linear programIn this manuscript, integer decisions are fixed by NSGA‐II and continuous variables are computed with a non‐linear programming solverThe hybrid method converges faster and more consistently to a better Pareto front approximation than alternative methods from the literature [ABSTRACT FROM AUTHOR] |
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| Database: |
Biomedical Index |