LEMMO: Hybridising rule induction and NSGA II for Multi-Objective Water Systems design

نویسندگان

  • L. Jourdan
  • D. W. Corne
  • D. Savic
  • G. Walters
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.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

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...

متن کامل

Preliminary Investigation of the 'Learnable Evolution Model' for Faster/Better Multiobjective Water Systems Design

The design of large scale water distribution systems is a very difficult optimisation problem which invariably requires the use of timeexpensive 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’ tec...

متن کامل

Multi-objective Pareto optimization of bone drilling process using NSGA II algorithm

Bone drilling process is one the most common processes in orthopedic surgeries and bone breakages treatment. It is also very frequent in dentistry and bone sampling operations. Bone is a complex material and the machining process itself is sensitive so bone drilling is one of the most important, common and sensitive processes in Biomedical Engineering field. Orthopedic surgeries can be improved...

متن کامل

Active Power Filter Design by a Novel Approach of Multi-Objective Optimization

This paper presents an innovative active power filter design method to simultaneously compensate the current harmonics and reactive power of a nonlinear load. The power filter integrates a passive power filter which is a RL low-pass filter placed in series with the load, and an active power filter which comprises an RL in series with an IGBT based voltage source converter. The filter is assumed...

متن کامل

Multi-objective optimization of nanofluid flow in microchannel heat sinks with triangular ribs using CFD and genetic algorithms

Abstract In this paper, multi-objective optimization (MOO) of Al2O3-water nanofluid flow in microchannel heat sinks (MCHS) with triangular ribs is performed using Computational Fluid Dynamics (CFD) techniques and Non-dominated Sorting Genetic Algorithms (NSGA II). At first, nanofluid flow is solved numerically in various MCHS with triangular ribs using CFD techniques. Finally, the CFD data will...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2005