Memes co‐evolution strategies for fast convergence in solving single machine scheduling problems

In recent years, researchers have become more aware of the significance and importance of memes in computational problem‐solving. It is now generally accepted that collectively, memes as a group or population undergo evolution just like genes, competition and collaboration. In this paper, we present...

全面介紹

Saved in:
書目詳細資料
Main Authors: Huang, Wei-Hsiu, Chang, Pei‐Chann, Lim, Meng-Hiot, Zhang, Zhenzhen
其他作者: School of Electrical and Electronic Engineering
格式: Article
語言:English
出版: 2013
主題:
在線閱讀:https://hdl.handle.net/10356/105005
http://hdl.handle.net/10220/17018
http://dx.doi.org/10.1080/00207543.2011.649799
標簽: 添加標簽
沒有標簽, 成為第一個標記此記錄!
實物特徵
總結:In recent years, researchers have become more aware of the significance and importance of memes in computational problem‐solving. It is now generally accepted that collectively, memes as a group or population undergo evolution just like genes, competition and collaboration. In this paper, we present a memes co‐evolutionary framework for solving the single machine total weighted tardiness problem. The mechanisms of memes co‐evolution serve to promote diversity not just in the solutions, but also within the memes that participate in the search. Our results show convincingly that the memes co‐evolution strategies are able to improve the performance in solving several difficult benchmarks of weighted tardiness single‐machine scheduling problems.