Improving Nonlinear Optimization Algorithms for BMP Implementation in a Combined Sewer System
| Autor: | Anas Sebti, Mauricio Carvallo Aceves, Saad Bennis, Musandji Fuamba |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Mathematical optimization
Engineering Linear programming business.industry 0208 environmental biotechnology Geography Planning and Development 02 engineering and technology Management Monitoring Policy and Law 020801 environmental engineering Nonlinear programming Technical performance Rain garden Retention basin Simulated annealing Optimization methods Combined sewer business Water Science and Technology Civil and Structural Engineering |
| Zdroj: | Journal of Water Resources Planning and Management. 142 |
| ISSN: | 1943-5452 0733-9496 |
| DOI: | 10.1061/(asce)wr.1943-5452.0000669 |
| Popis: | Implementing best management practices (BMP) on watersheds could help mitigate the effects of urbanization and climate change on the hydrological cycle. Techniques such as retention ponds, rain gardens, infiltration trenches, and green roofs vary in technical performance, space requirements, and cost. The trade-offs between these present a challenge toward BMP selection and placement, therefore requiring optimization. Three optimization methods were applied for BMP implementation on a combined sewer: linear programming (LP); genetic algorithm (GA); and simulated annealing (SA). LP served as a reference point. The SA solution was only marginally better, 4.7% cheaper, whereas GA’s solution was 17.9% more expensive after computations froze at a local minimum; both methods required approximately 18 h of computational time. A second round of optimization used the solution from LP as a starting point. This modification significantly increased the performance of GA, providing a new solution that was 14% ... |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|