计算机科学
进化算法
客观性(哲学)
领域(数学)
分类学(生物学)
管理科学
运筹学
数据科学
人工智能
机器学习
生态学
数学
认识论
纯数学
哲学
经济
生物
作者
Shouyong Jiang,Juan Zou,Shengxiang Yang,Xin Yao
摘要
Evolutionary dynamic multi-objective optimisation (EDMO) is a relatively young but rapidly growing area of investigation. EDMO employs evolutionary approaches to handle multi-objective optimisation problems that have time-varying changes in objective functions, constraints, and/or environmental parameters. Due to the simultaneous presence of dynamics and multi-objectivity in problems, the optimisation difficulty for EDMO has a marked increase compared to that for single-objective or stationary optimisation. After nearly two decades of community effort, EDMO has achieved significant advancements on various topics, including theoretic research and applications. This article presents a broad survey and taxonomy of existing research on EDMO. Multiple research opportunities are highlighted to further promote the development of the EDMO research field.
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