A macro-evolutionary multi-objective immune algorithm with application to optimal allocation of water resources in Dongjiang River basins, South China |
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| Authors: | Dedi Liu Shenglian Guo Xiaohong Chen Quanxi Shao Qihua Ran Xingyuan Song Zhaoli Wang |
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| Institution: | (1) State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan, 430072, China;(2) College of Water Resources and Hydroelectric Engineering, Wuhan University, Wuhan, 430072, China;(3) Center for Water Resource and Environment, Sun Yat-sen University, Guangzhou, 510275, China;(4) CSIRO Mathematical and Information Sciences, Private Bag 5, Wembley, WA, 6913, Australia;(5) Institute of Hydrology and Water Resources, Zhejiang University, Hangzhou, 310058, China;(6) The State Key Laboratory of Subtropical Building Science, South China University of Technology, Guangzhou, China; |
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| Abstract: | Macro-evolution is a new kind of high-level species evolution inspired by the dynamics of species extinction and diversification
at large time scales. Immune algorithms are a set of computational systems inspired by the defense process of the biological
immune system. By taking advantage of the macro-evolutionary algorithm and immune learning of artificial immune systems, this
article proposes a macro-evolutionary multi-objective immune algorithm (MEMOIA) for optimizing multi-objective allocation
of water resources in river basins. A benchmark test problem, namely the Viennet problem, is utilized to evaluate the performance
of the proposed new algorithm. The study indicates that the proposed algorithm yields a much better spread of solutions and
converges closer to the true Pareto frontier compared with The Non-dominated Sorting Genetic Algorithm and Improving the Strength
Pareto Evolutionary Algorithm. MEMOIA is applied to a water allocation problem in the Dongjiang River basin in southern China,
with three objectives named economic interests (OF
1), water shortages (OF
2) and the amount of organic pollutants in water (OF
3). The results demonstrate the capabilities of MEMOIA as well as its suitability as a viable alternative for enhanced water
allocation and management in a river basin. |
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