A DEA-GA multi-objective scheduling algorithm for Chip-Multiprocessor

摘要：

　　In this paper, a Data Envelopment analysis based Genetic Algorithm (DEA-GA) is proposed for multi-objective scheduling on Chip-Muitiprocessor.The proposal adopts modified GA as the searching heuristic to explore the solution space, and the fitness of each individual (schedule) is evaluated using the DEA approach.Three of the schedule metrics, namely makespan, energy and load balance are used to construct the multi-input multi-output Decision Making Units in the DEA, and the BCC super efficiency of each schedule is calculated.In the modified genetic algorithm, the metapopulation is divided into three subpopulations each optimizing a single metric.The top performance individuals in each subpopulation are then regrouped and applied DEA evaluation.Comparing to other multi-objective scheduling algorithm in simulations, our proposal always produces more efficient schedule solutions.

关键词： DEA efficiency Genetic Algorithm multi-objective scheduling Chip Multiprocessor

作者: Song Chai Yubai Li Chang Wu Jian Wang

作者单位: School of Communication and Information Engineering,University of Electronic Science and Technology of China,Chengdu,China

会议类型: 国际会议

会议名称: 2013 2nd International Conference on Science and Social Research (2013年第二届科学与社会研究国际会议)(ICSSR2013)

会议地点: 北京

会议语种:英文

页码: 666-670

在线出版日期: 2013-07-13（万方平台首次上网日期，不代表论文的发表时间）