An Improved Parallelized Multi-Objective Optimization Method for Complex Geographical Spatial Sampling: AMOSA-II

Complex geographical spatial sampling usually encounters various multi-objective optimization problems, for which effective multi-objective optimization algorithms are much needed to help advance the field. To improve the computational efficiency of the multi-objective optimization process, the arch...

詳細記述

書誌詳細

出版年:	ISPRS International Journal of Geo-Information
主要な著者:	Xiaolan Li, Bingbo Gao, Zhongke Bai, Yuchun Pan, Yunbing Gao
フォーマット:	論文
言語:	英語
出版事項:	MDPI AG 2020-04-01
主題:	multi-objective optimization AMOSA-II multiple Markov chains parallelization
オンライン･アクセス:	https://www.mdpi.com/2220-9964/9/4/236