Work

Implementation of a Prototype Genetic Algorithm for Optimal, Coordinated Operation of Stormwater Pump Stations

Year: 2025

Type: article

Abstract: As heavy rainfall events increase, the need for efficient operation of urban drainage systems is becoming critical. In this study, we implement a prototype model designed to generate an optimal, coordinated operating schedule for an urban drainage system with the objective of minimizing system-wide flood damage. The proposed model rapidly estimates the total damage reduction by combining precomputed flood mitigation performance curves for each station with period-specific initial inundation indicators, and then selects the schedule that maximizes total damage reduction. The model is implemented as a Genetic Algorithm (GA) in a Python/DEAP environment and validated using a hypothetical pilot area. Validation using a hypothetical case confirmed that by rationally excluding inferior combinations of solutions, the optimization mechanism can be appropriately embedded in pump station operational decision-making, and its short execution time indicates the potential for deployment as a tool for real-time operation.

Source: Korean Society of Hazard Mitigation

DOI: 10.9798/kosham.2025.25.6.407

Authors: Dong Jun Kim, Jonghwan Kang, Jung Ho Lee, Hwan Don Jun, Jae Hee Kim

Institutions: Seoul National University of Science and Technology, Jeonbuk National University, Hanbat National University

Language: English

Topic: Urban Stormwater Management Solutions

Subfield: Environmental Engineering

Field: Environmental Science

Domain: Physical Sciences

SDGs: Clean water and sanitation, Sustainable cities and communities, Industry, innovation and infrastructure

Open Access status: diamond

Funder: Ministry of the Interior and Safety