A Genetic Algorithm Parallel Strategy for Optimizing the Operation of Reservoir with Multiple Eco-environmental Objectives

Duan Chen (), Qiuwen Chen, Arturo S. Leon and Ruonan Li
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Duan Chen: Changjiang River Scientific Research Institute
Qiuwen Chen: CEER Nanjing Hydraulic Research Institute
Arturo S. Leon: Oregon State University
Ruonan Li: Chinese Academy of Sciences

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2016, vol. 30, issue 7, No 2, 2127-2142

Abstract: Abstract Optimizing the operation of reservoir involving ecological and environmental (eco-environmental) objectives is challenging due to the often competing social-economic objectives. Non-dominated Sorting Genetic Algorithm-II is a popular method for solving multi-objective optimization problems. However, within a complex search space, the NSGA-II population (i.e., a group of candidate solutions) may be trapped in local optima as the population diversity is progressively reduced. This study proposes a computational strategy that operates several parallel populations to maintain the diversity of the candidate solutions. An improved version of the NSGA-II, called c-NSGA-II is implemented by incorporating multiple recombination operators. The parallel strategy is then coupled into the routine of the c-NSGA-II and applied to the operation of the Qingshitan reservoir (Southwest of China) which includes three eco-environmental and two social-economic objectives. Three metrics (convergence, diversity, and hyper volume index) are used for evaluating the optimization performances. The results show that the proposed parallel strategy significantly improves the solution quality in both convergence and diversity. Two characteristic schemes are identified for the operation of the Qingshitan reservoir for trade-off between the eco-environmental and social-economic objectives.

Keywords: Reservoir operation; Ecological and environmental objectives; NSGA-II; Parallel strategy (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s11269-016-1274-1

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