Redundant binary codes in genetic algorithms: multi-objective design optimization of water distribution networks
Genetic algorithms have been shown to be highly effective for optimization problems in various disciplines, and binary coding is generally adopted as it is straightforward to implement and lends itself to problems with discrete-valued decision variables. However, a difficulty associated with binary...
Enregistré dans:
Auteur principal: | Tiku T. Tanyimboh |
---|---|
Format: | article |
Langue: | EN |
Publié: |
IWA Publishing
2021
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/8a0b4d8c8e7b43f1aba6862e7b717aca |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Comparing deep learning with several typical methods in prediction of assessing chlorophyll-a by remote sensing: a case study in Taihu Lake, China
par: Xiaolan Zhao, et autres
Publié: (2021) -
Corrigendum: H2Open Journal 2 (1), 125–136: Nutrient removal using spent coconut husks, Trina Halfhide, Lorale J. Lalgee, Karen Seudat Singh, Joshua Williams, Matthew Sealy, Anton Manoo and Azad Mohammed, doi: 10.2166/h2oj.2019.011
Publié: (2021) -
Editorial: Important news about this journal
Publié: (2021) -
Editorial: Integrated water management for enhanced water quality and reuse to create a sustainable future
par: Eldon R. Rene, et autres
Publié: (2021) -
Erratum: Water Supply 20 (7), 2484–2498: Historic hydraulic works: paradigms of traditional good water governance, integrity and sustainability, Feirouz Megdiche-Kharrat, Xiao Yun Zheng, Mohamed Moussa, Zhang Famin and Andreas N. Angelakis
Publié: (2021)