LEMMO: Hybridising rule induction and NSGA II for Multi-Objective Water Systems design
نویسندگان
چکیده
Many studies use genetic algorithms to model water distribution network and they give some interesting results. Recent studies propose a multi-objective model of the problem. But one of the drawbacks of genetic algorithm both mono and multi-objective is the extensive use of the evaluation process. In water systems design, the evaluation of the quality of a water distribution network requires a time expensive simulation. These article deals with the use of machine learning to boost the convergence of a multi-objective genetic algorithm in the particular context of water systems design. By testing the method called LEMMO, on small and large networks we prove the interest of our algorithm to accelerate the search of a multi-objective genetic algorithm.
منابع مشابه
LEMMO : Hybridising rule induction and NSGA II for Mutli- Objective Water Systems design
The design of large scale water distribution systems is a very difficult optimisation problem which invariably requires the use of time expensive simulations within the fitness function. The need to accelerate optimisation for such problems has not so far been seriously tackled. However, this is a very important issue, since as MOEAs become more and more recognised as the ‘industry standard’ te...
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