Urban Drainage Networks Rehabilitation Using Multi-Objective Model and Search Space Reduction Methodology
| Autor: | F. Javier Martínez-Solano, Pedro L. Iglesias-Rey, Ulrich A. Ngamalieu-Nengoue |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Mathematical optimization
010504 meteorology & atmospheric sciences Process (engineering) Computer science 0207 environmental engineering 09.- Desarrollar infraestructuras resilientes promover la industrialización inclusiva y sostenible y fomentar la innovación 02 engineering and technology 01 natural sciences Multi-objective optimization lcsh:Technology problem size reduction rehabilitation Reduction (complexity) Genetic algorithm General Materials Science Drainage 020701 environmental engineering extreme rainfalls drainage networks 0105 earth and related environmental sciences Civil and Structural Engineering Multiobjective optimization Problem size reduction 06.- Garantizar la disponibilidad y la gestión sostenible del agua y el saneamiento para todos lcsh:T MECANICA DE FLUIDOS Rehabilitation Sorting Pareto principle Building and Construction Storm Water Management Model Geotechnical Engineering and Engineering Geology Computer Science Applications multi-objective optimization SWMM Extreme rainfalls Drainage networks |
| Zdroj: | Infrastructures Volume 4 Issue 2 Infrastructures, Vol 4, Iss 2, p 35 (2019) RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia instname |
| ISSN: | 2412-3811 |
| DOI: | 10.3390/infrastructures4020035 |
| Popis: | The drainage network always needs to adapt to environmental and climatic conditions to provide best quality services. Rehabilitation combining pipes substitution and storm tanks installation appears to be a good solution to overcome this problem. Unfortunately, the calculation time of such a rehabilitation scenario is too elevated for single-objective and multi-objective optimization. In this study, a methodology composed by search space reduction methodology whose purpose is to decrease the number of decision variables of the problem to solve and a multi-objective optimization whose purpose is to optimize the rehabilitation process and represent Pareto fronts as the result of urban drainage networks optimization is proposed. A comparison between different model results for multi-objective optimization is made. To obtain these results, Storm Water Management Model (SWMM) is first connected to a Pseudo Genetic Algorithm (PGA) for the search space reduction and then to a Non-Dominated Sorting Genetic Algorithm II (NSGA-II) for multi-objective optimization. Pareto fronts are designed for investment costs instead of flood damage costs. The methodology is applied to a real network in the city of Medellin in Colombia. The results show that search space reduction methodology provides models with a considerably reduced number of decision variables. The multi-objective optimization shows that the models&rsquo results used after the search space reduction obtain better outcomes than in the complete model in terms of calculation time and optimality of the solutions. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|