Aging collection systems with asset condition and capacity deficiencies and expanding systems with anticipated future capacity deficiencies typically have a large range of improvement alternatives and planning scenarios available for analysis. Traditional “trial-and-error” scenario modeling is able to handle only a relatively small number of scenarios and does not provide a comprehensive and defensible approach to evaluate the vast number of available alternatives. Genetic Algorithm (GA) optimization using Optimizer WCSTM (formal optimization software by Optimatics) provides a framework for undertaking a comprehensive analysis of master plan alternatives that considers system-wide interactions and life-cycle costs.
Optimizer links to the hydraulic model and detailed life-cycle cost data and evaluates many thousands of improvement alternatives. In a single analysis, cloud-computing is used to run thousands of solution permutations to identify those solutions that meet the planning and performance criteria at least cost. Moreover, once formulated, the optimization model can be used to efficiently run scenarios and sensitivity analyses to develop alternate solutions with distinctly different characteristics. To help maintain rate stability and maximize return on investment, the optimization technology can also be used to prioritize capital works schedules to maximize performance improvements within each implementation period and budget.
Compared to traditional trial-and-error assessment of alternatives, GA optimization
Master plans developed using on GA optimization consistently achieve life-cycle cost savings on the order of 15 to 30% compared to trial-and-error solutions, are more defensible given that many thousands of alternatives are evaluated against total cost and hydraulic performance and can be adapted more easily over time due to the flexibility of updating the optimization model and rerunning it as new data become available. The Optimizer technology provides most value when applied to collection systems with significant CSOs or SSOs and a wide array of control measure alternatives. It is best applied on a system-wide basis to initially perform a high-level review of alternatives and then a more detailed optimization of alternatives once the initial high-level screening is complete.
The effective application of GA optimization requires the experience of a specialist user. The WCS Engineering team has specialized in GA optimization using Optimatics’ software since 2003 and has completed approximately 50 optimization projects throughout the United States, Australia, and New Zealand. On each and every project we are committed to achieving and surpassing our client's expectations. We have an excellent track record with respect to meeting budgets, working within tight project schedules, and delivering robust and cost-effective solutions for our clients.
CIP OPTIMIZATION is an advanced modeling and economic analysis technology that utilises cloud computing and enables the analysis of thousands of alternatives, resulting in the best possible combination of capital improvements based on cost and hydraulic performance.
Once formulated, the optimization model can be used to efficiently run scenarios and sensitivity analysis. Solutions can be easily updated as more data becomes available and assumptions are refined.
In contrast, traditional "trial-and-error" scenario modeling limits the number of alternatives that can be thoroughly investigated and any change to inputs or assumptions requires extensive rework.
Water Distribution and Wastewater Collection Systems
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