TY - JOUR
T1 - Scheduling fully parallel jobs
AU - Wang, Kai
AU - Chau, Vincent
AU - Li, Minming
N1 - Publisher Copyright:
© 2018, Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2018/12/1
Y1 - 2018/12/1
N2 - We consider the following scheduling problem. We have m identical machines, where each machine can accomplish one unit of work at each time unit. We have a set of n fully parallel jobs, where each job j has sj units of workload, and each unit workload can be executed on any machine at any time unit. A job is considered complete when its entire workload has been executed. The objective is to find a schedule that minimizes the total weighted completion time ∑ wjCj, where wj is the weight of job j and Cj is the completion time of job j. We provide theoretical results for this problem. First, we give a PTAS of this problem with fixed m. We then consider the special case where wj= sj for each job j, and we show that it is polynomial solvable with fixed m. Finally, we study the approximation ratio of a greedy algorithm, the Largest-Ratio-First algorithm. For the special case, we show that the approximation ratio depends on the instance size, i.e. n and m, while for the general case where jobs have arbitrary weights, we prove that the upper bound of the approximation ratio is 1+m-1m+2.
AB - We consider the following scheduling problem. We have m identical machines, where each machine can accomplish one unit of work at each time unit. We have a set of n fully parallel jobs, where each job j has sj units of workload, and each unit workload can be executed on any machine at any time unit. A job is considered complete when its entire workload has been executed. The objective is to find a schedule that minimizes the total weighted completion time ∑ wjCj, where wj is the weight of job j and Cj is the completion time of job j. We provide theoretical results for this problem. First, we give a PTAS of this problem with fixed m. We then consider the special case where wj= sj for each job j, and we show that it is polynomial solvable with fixed m. Finally, we study the approximation ratio of a greedy algorithm, the Largest-Ratio-First algorithm. For the special case, we show that the approximation ratio depends on the instance size, i.e. n and m, while for the general case where jobs have arbitrary weights, we prove that the upper bound of the approximation ratio is 1+m-1m+2.
KW - Approximation ratio
KW - Integer parallel units
KW - Parallel jobs
KW - Total weighted completion time
UR - https://www.scopus.com/pages/publications/85045465742
U2 - 10.1007/s10951-018-0563-3
DO - 10.1007/s10951-018-0563-3
M3 - 文章
AN - SCOPUS:85045465742
SN - 1094-6136
VL - 21
SP - 619
EP - 631
JO - Journal of Scheduling
JF - Journal of Scheduling
IS - 6
ER -