Multi-objective optimization of water supply network rehabilitation with non-dominated sorting Genetic Algorithm-II |
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| Authors: | Xi Jin Jie Zhang Jin-liang Gao Wen-yan Wu |
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| Institution: | (1) School of Municipal and Environment Engineering, Harbin Institute of Technology, Harbin, 150090, China;(2) Faculty of Computing, Engineering and Technology, Staffordshire University, Beaconside, Stafford, UK |
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| Abstract: | 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.
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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| Keywords: | Water supply system Water supply network Optimal rehabilitation Multi-objective Non-dominated sorting Genetic Algorithm (NSGA) |
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