Most consequential water management questions are, at their core, optimization problems: how to allocate scarce water across competing demands, how to size and schedule infrastructure, and how to operate systems reliably over time. These problems are typically nonlinear, high-dimensional, and constrained.
This theme develops and benchmarks metaheuristic and evolutionary optimization methods — including the Honey-Bees Mating Optimization (HBMO) algorithm — and applies them to real water resources systems. The emphasis is on methods that balance solution quality, computational cost, and interpretability for decision-makers.
- Algorithm design and rigorous benchmarking on engineering problems
- Single- and multi-objective formulations of water systems
- Coupling simulation models with optimization engines