no code implementations • 13 Oct 2023 • Dan-Xuan Liu, Yu-Ran Gu, Chao Qian, Xin Mu, Ke Tang
In this paper, we propose a new framework MR-EMO based on Evolutionary Multi-objective Optimization, which reformulates Migrant Resettlement as a bi-objective optimization problem that maximizes the expected number of employed migrants and minimizes the number of dispatched migrants simultaneously, and employs a Multi-Objective Evolutionary Algorithm (MOEA) to solve the bi-objective problem.
1 code implementation • 18 Oct 2021 • Chao Qian, Dan-Xuan Liu, Zhi-Hua Zhou
Experiments on the applications of web-based search, multi-label feature selection and document summarization show the superior performance of the GSEMO over the state-of-the-art algorithms (i. e., the greedy algorithm and local search) under both static and dynamic environments.
no code implementations • 20 Apr 2021 • Chao Qian, Dan-Xuan Liu, Chao Feng, Ke Tang
Evolutionary algorithms (EAs) are general-purpose optimization algorithms, inspired by natural evolution.