Through the transformation of hydraulic constraints into the objective functions associated with a water supply network rehabilitation problem, a non-dominated sorting Genetic Algorithm-II (NSGA-II) can be used to solve the altered multi-objective optimization model. The introduction of NSGA-II into water supply network optimal rehabilitation problem solves the conflict between one fitness value of standard genetic algorithm (SGA) and multi-objectives of rehabilitation problem. And the uncertainties brought by using weight coefficients or punish functions in conventional methods are controlled. And also by introduction of artificial inducement mutation (AIM) operation, the convergence speed of population is accelerated; this operation not only improves the convergence speed, but also improves the rationality and feasibility of solutions.
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Project supported by the Natural Science Key Foundation of Heilongjiang Province of China (No. ZJG0503) and China-UK Science Network from Royal Society UK
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Jin, X., Zhang, J., Gao, Jl. et al. Multi-objective optimization of water supply network rehabilitation with non-dominated sorting Genetic Algorithm-II. J. Zhejiang Univ. Sci. A 9, 391–400 (2008). https://doi.org/10.1631/jzus.A071448
- Water supply system
- Water supply network
- Optimal rehabilitation
- Non-dominated sorting Genetic Algorithm (NSGA)