Developments in Multi-Objective Dynamic Optimization Algorithm for Design of Water Distribution Mains

被引:0
|
作者
Amin Minaei
Adell Moradi Sabzkouhi
Ali Haghighi
Enrico Creaco
机构
[1] University of Pavia,DICAr
[2] Agricultural Sciences and Natural Resources University of Khuzestan,Dept. of Hydraulic Engineering
[3] Shahid Chamran University of Ahvaz,Department of Civil Engineering, Faculty of Engineering
来源
关键词
Water distribution networks; Design; Dynamic optimization; Engineering judgment; Efficiency; Multi-phase;
D O I
暂无
中图分类号
学科分类号
摘要
This paper presents some developments in the optimization effectiveness for the dynamic design of water distribution networks (WDNs), tackled employing multi-objective genetic algorithms. Unlike the traditional single-phase design, the dynamic multi-phase design operates on planning WDN upgrades on short time intervals, also called phases or stages, while fitting them into a long-term planning horizon, thus requiring bespoke research efforts for the improvement of the optimization effectiveness. A modified version of dynamic NSGA-II optimization is introduced here, including: no penalty on the objective functions for infeasible solutions, adoption of engineering judgments in the construction of optimization individuals, restricting the number of parallel pipes at each site. This results in the improvement of convergence speed and solution quality in two case studies with different complexities.
引用
收藏
页码:2699 / 2716
页数:17
相关论文
共 50 条
  • [31] Dynamic multi-objective optimization model and algorithm for logistics network
    Wang Y.
    Shi Q.
    Song W.
    Hu Q.
    Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS, 2020, 26 (04): : 1142 - 1150
  • [32] Dynamic multi-objective optimization algorithm based decomposition and preference
    Hu, Yaru
    Zheng, Jinhua
    Zou, Juan
    Jiang, Shouyong
    Yang, Shengxiang
    INFORMATION SCIENCES, 2021, 571 : 175 - 190
  • [33] A dynamic multi-objective optimization evolutionary algorithm with adaptive boosting
    Peng, Hu
    Xiong, Jianpeng
    Pi, Chen
    Zhou, Xinyu
    Wu, Zhijian
    SWARM AND EVOLUTIONARY COMPUTATION, 2024, 89
  • [34] An evolutionary algorithm for solving dynamic multi-objective optimization problem
    Liu, Chunan
    Dou, Xiaoxia
    Journal of Computational Information Systems, 2013, 9 (07): : 2837 - 2844
  • [35] A dynamic tri-population multi-objective evolutionary algorithm for constrained multi-objective optimization problems
    Yang, Yongkuan
    Yan, Bing
    Kong, Xiangsong
    EVOLUTIONARY INTELLIGENCE, 2024, 17 (04) : 2791 - 2806
  • [36] Application of multi-objective optimization algorithm in multidisciplinary optimization of ship design
    Hao, Zhailiu
    Liu, Zuyuan
    Feng, Baiwei
    Ship Building of China, 2014, 55 (03) : 53 - 63
  • [37] Multi-objective optimization algorithm based on marginal distribution estimation
    Lab. of Nature Inspired Computation and Application, University of Science and Technology of China, Hefei 230027, China
    Dianzi Yu Xinxi Xuebao, 2007, 11 (2683-2687):
  • [38] Multi-Objective Optimization with Estimation of Distribution Algorithm in a Noisy Environment
    Shim, Vui Ann
    Tan, Kay Chen
    Chia, Jun Yong
    Al Mamun, Abdullah
    EVOLUTIONARY COMPUTATION, 2013, 21 (01) : 149 - 177
  • [39] Robust airfoil optimization with multi-objective estimation of distribution algorithm
    Zhong Xiaoping
    Ding Jifeng
    Li Weiji
    Zhang Yong
    CHINESE JOURNAL OF AERONAUTICS, 2008, 21 (04) : 289 - 295
  • [40] Multi-objective Quantum Genetic Algorithm in WSNs Distribution Optimization
    Wen, Hao
    Ren, Hong-liang
    FIFTH INTERNATIONAL CONFERENCE ON MACHINE VISION (ICMV 2012): ALGORITHMS, PATTERN RECOGNITION AND BASIC TECHNOLOGIES, 2013, 8784