考虑带服务等级的三台平行机排序问题.预先赋予每台机器和每个任务一个服务等级(grade of service)标号.每个任务只能被某台服务等级不高于该任务服务等级的机器加工.目标是最小化最大机器完工时间.本文给出了求解这个问题的算法.并证...考虑带服务等级的三台平行机排序问题.预先赋予每台机器和每个任务一个服务等级(grade of service)标号.每个任务只能被某台服务等级不高于该任务服务等级的机器加工.目标是最小化最大机器完工时间.本文给出了求解这个问题的算法.并证明算法的最坏情况界不超过54+12k,其中k是算法中预先给定的迭代次数.已有的算法仅为32.展开更多
This work is aimed at investigating the online scheduling problem on two parallel and identical machines with a new feature that service requests from various customers are entitled to many different grade of service ...This work is aimed at investigating the online scheduling problem on two parallel and identical machines with a new feature that service requests from various customers are entitled to many different grade of service (GoS) levels, so each job and machine are labelled with the GoS levels, and each job can be processed by a particular machine only when its GoS level is no less than that of the machine. The goal is to minimize the makespan. For non-preemptive version, we propose an optimal online al-gorithm with competitive ratio 5/3. For preemptive version, we propose an optimal online algorithm with competitive ratio 3/2.展开更多
文摘考虑带服务等级的三台平行机排序问题.预先赋予每台机器和每个任务一个服务等级(grade of service)标号.每个任务只能被某台服务等级不高于该任务服务等级的机器加工.目标是最小化最大机器完工时间.本文给出了求解这个问题的算法.并证明算法的最坏情况界不超过54+12k,其中k是算法中预先给定的迭代次数.已有的算法仅为32.
基金Project supported by the National Natural Science Foundation of China (No. 10271110) and the Teaching and Research Award Pro-gram for Outstanding Young Teachers in Higher Education, Institu-tions of MOE, China
文摘This work is aimed at investigating the online scheduling problem on two parallel and identical machines with a new feature that service requests from various customers are entitled to many different grade of service (GoS) levels, so each job and machine are labelled with the GoS levels, and each job can be processed by a particular machine only when its GoS level is no less than that of the machine. The goal is to minimize the makespan. For non-preemptive version, we propose an optimal online al-gorithm with competitive ratio 5/3. For preemptive version, we propose an optimal online algorithm with competitive ratio 3/2.
