Abstract
Problems of water resource systems entail many inherent objectives from cost-related to environmental issues, which are usually in conflict and should be addressed simultaneously in decision-making. Multi-objective optimization algorithms aim to simultaneously satisfy two or more objectives and provide a set of optimal solutions for multi-objective optimization problems. Such algorithms can also improve the accuracy of simulation models, such as artificial neural network and adaptive neuro fuzzy interface system. This chapter first presents essential definitions in multi-objective algorithms and their applications in different areas of water resources systems (i.e., model calibration, water distribution network, reservoir operation and management, water quality, water structure design, and groundwater). It then evaluates performance of a recently proposed and two well-known multi-objective algorithms for solving three problems in the optimal operation of a real multipurpose dam.
| Original language | English |
|---|---|
| Title of host publication | Springer Water |
| Publisher | Springer Nature |
| Pages | 275-303 |
| Number of pages | 29 |
| DOIs | |
| Publication status | Published - 2021 |
Publication series
| Name | Springer Water |
|---|---|
| ISSN (Print) | 2364-6934 |
| ISSN (Electronic) | 2364-8198 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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SDG 6 Clean Water and Sanitation
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SDG 9 Industry, Innovation, and Infrastructure
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SDG 11 Sustainable Cities and Communities
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SDG 12 Responsible Consumption and Production
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SDG 13 Climate Action
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SDG 17 Partnerships for the Goals
Keywords
- Adaptive neuro fuzzy interface system
- Artificial neural network
- Optimization algorithms
- Water resources systems
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