Multi-objective Optimisation Design of Water Distribution Systems:Comparison of Two Evolutionary Algorithms

被引:3
|
作者
Haixing Liu
Jing Lu
Ming Zhao
Yixing Yuan
机构
[1] SchoolofMunicipalandEnvironmentalEngineering,HarbinInstituteofTechnology
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In order to compare two advanced multi-objective evolutionary algorithms,a multi-objective water distribution problem is formulated in this paper.The multi-objective optimization has received more attention in the water distribution system design.On the one hand the cost of water distribution system including capital,operational,and maintenance cost is mostly concerned issue by the utilities all the time;on the other hand improving the performance of water distribution systems is of equivalent importance,which is often conflicting with the previous goal.Many performance metrics of water networks are developed in recent years,including total or maximum pressure deficit,resilience,inequity,probabilistic robustness,and risk measure.In this paper,a new resilience metric based on the energy analysis of water distribution systems is proposed.Two optimization objectives are comprised of capital cost and the new resilience index.A heuristic algorithm,speedconstrained multi-objective particle swarm optimization( SMPSO) extended on the basis of the multi-objective particle swarm algorithm,is introduced to compare with another state-of-the-art heuristic algorithm,NSGA-II.The solutions are evaluated by two metrics,namely spread and hypervolume.To illustrate the capability of SMPSO to efficiently identify good designs,two benchmark problems( two-loop network and Hanoi network) are employed.From several aspects the results demonstrate that SMPSO is a competitive and potential tool to tackle with the optimization problem of complex systems.
引用
收藏
页码:30 / 38
页数:9
相关论文
共 50 条
  • [41] Water Quality Based Multi-objective Optimal Design of Water Distribution Systems
    Shokoohi, Meisam
    Tabesh, Massoud
    Nazif, Sara
    Dini, Mehdi
    WATER RESOURCES MANAGEMENT, 2017, 31 (01) : 93 - 108
  • [42] Water Quality Based Multi-objective Optimal Design of Water Distribution Systems
    Meisam Shokoohi
    Massoud Tabesh
    Sara Nazif
    Mehdi Dini
    Water Resources Management, 2017, 31 : 93 - 108
  • [43] Evolutionary Dynamic Multi-objective Optimisation: A Survey
    Jiang, Shouyong
    Zou, Juan
    Yang, Shengxiang
    Yao, Xin
    ACM COMPUTING SURVEYS, 2023, 55 (04)
  • [44] Multi-objective evolutionary optimisation of microwave oscillators
    Brito, LDC
    de Carvalho, P
    Bermúdez, LA
    ELECTRONICS LETTERS, 2004, 40 (11) : 677 - 678
  • [45] On the Effect of Populations in Evolutionary Multi-Objective Optimisation
    Giel, Oliver
    Lehre, Per Kristian
    EVOLUTIONARY COMPUTATION, 2010, 18 (03) : 335 - 356
  • [46] Evolutionary Multi-objective Optimisation in Neurotrajectory Prediction
    Galvan, Edgar
    Stapleton, Fergal
    APPLIED SOFT COMPUTING, 2023, 146
  • [47] A Parallel Evolutionary System for Multi-objective Optimisation
    Hamdan, Mohammad
    Rudolph, Gunter
    Hochstrate, Nicola
    2020 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2020,
  • [48] Evolutionary multi-objective optimisation with a hybrid representation
    Okabe, T
    Jin, Y
    Sendhoff, B
    CEC: 2003 CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-4, PROCEEDINGS, 2003, : 2262 - 2269
  • [49] Evolutionary Multi-objective Optimisation of Business Processes
    Tiwari, Ashutosh
    Vergidis, Kostas
    Turner, Chris
    SOFT COMPUTING IN INDUSTRIAL APPLICATIONS - ALGORITHMS, INTEGRATION, AND SUCCESS STORIES, 2010, 75 : 293 - 301
  • [50] Evolutionary multi-objective optimisation by diversity control
    Kulvanit, Pasan
    Piroonratana, Theera
    Chaiyaratana, Nachol
    Laowattana, Djitt
    COMPUTER SCIENCE - THEORY AND APPLICATIONS, 2006, 3967 : 447 - 456