Multi-objective intelligent optimization algorithms have been widely used in reservoir management and operation. However, selection of various emerging algorithms is still one of the research hotspots during reservoir management and operation. With highly simplified problems, many studies emphasized on the practicability of algorithms in reservoir optimization operation. Further studies are still needed in algorithm selection, algorithm performance and multi-objective optimization, especially. In this paper we selected some widely used multi-objective algorithms, i.e. NSGA-II and DEMO, and analysed, compared and evaluated their applications in terms of the number of decision variables and the constraint handling. This study helps to select proper optimization algorithms in reservoir optimization operation.
Key words
reservoir operation /
multi-objective /
NSGA-II /
DEMO /
constraint handling
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References
[1] 覃 晖, 周建中, 王光谦,等. 基于多目标差分进化算法的水库多目标防洪调度研究[J]. 水利学报,2009,40(5):513-519.(QIN Hui, ZHOU Jian-zhong, WANG Guang-qian, et al. Multi-objective Optimization of Reservoir Flood Dispatch Based on Multi-objective Differential Evolution Algorithm[J]. Shuili Xuebao, 2009, 40(5): 513-519. (in Chinese))
[2] 张志刚,马光文. 基于NSGA-Ⅱ算法的多目标水火电站群优化调度模型研究[J]. 水力发电学报,2010,29(1):213-218. (ZHANG Zhi-gang, MA Guang-wen. Study on Optimal Scheduling Model of NSGA-Ⅱ Algorithm for System of Hydro and Thermal Power Plants[J]. Journal of Hydroelectric Engineering, 2010, 29(1): 213-218. (in Chinese))
[3] 肖 刚,解建仓,罗军刚. 基于改进NSGAII 的水库多目标防洪调度算法研究[J]. 水力发电学报,2012,31(5):77-83. (XIAO Gang,XIE Jian-cang,LUO Jun-gang. Improved NSGAII Algorithm for Flood Dispatching of Multi-objectives Reservoir[J]. Journal of Hydroelectric Engineering, 2012, 31(5):77-83.(in Chinese))
[4] SRINIVAS N,DEB K.Multi-objective Function Optimization Using Non-dominated Sorting Genetic Algorithms[J]. Evolutionary Computation, 1995, 2(3):221-248.
[5] DEB K, PRATAP A, AGARWAL S, et al. A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II[J]. IEEE Transactions on Evolutionary Computation, 2002, 6(2): 182-197.
[6] ROBI T, FILIPI B. DEMO: Differential Evolution for Multiobjective Optimization[C]∥Proceedings of the 3rd International Conference on Evolutionary Multi-Criterion Optimization (EMO 2005), Guanajuato, Mexico, March 9-11, 2005: 520-533.
[7] TU AR T, FILIPI B. Differential Evolution Versus Genetic Algorithms in Multiobjective Optimization[C]∥Proceedings of the 4th International Conference on Evolutionary Multi-Criterion Optimization (EMO 2007), Matsushima/Sendai, Japan, March 5-8, 2007: 257-271.
[8] ZITZLER E, THIELE L. Multiobjective Optimization Using Evolutionary Algorithms: A Comparative Study[J]. Parallel Problem Solving from Nature: PPSN V Lecture Notes in Computer Science, 1998, (1498): 292-301.
[9] DEB K. Multi-objective Optimization Using Evolutionary Algorithms[M]. New York: John Wiley & Sons, 2001.
[10]SCHOTT JR. Fault Tolerant Design Using Single and Multicriteria Genetic Algorithm Optimization[M]. Cambridge: Massachusetts Institute of Technology, 1995.
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