A note on the preemptive scheduling to minimize total completion time with release time and deadline constraints

2014 ◽  
Vol 18 (3) ◽  
pp. 315-323 ◽  
Author(s):  
Long Wan ◽  
Jinjiang Yuan ◽  
Zhichao Geng
Keyword(s):  
Completion Time ◽  
Total Completion Time ◽  
Release Time ◽  
Preemptive Scheduling ◽  
Deadline Constraints

scholarly journals Minimizing Total Completion Time For Preemptive Scheduling With Release Dates And Deadline Constraints

2014 ◽  
Vol 39 (1) ◽  
pp. 17-26 ◽  
Author(s):  
Cheng He ◽  
Hao Lin ◽  
Yixun Lin ◽  
Junmei Dou
Keyword(s):  
Completion Time ◽  
Total Completion Time ◽  
Release Dates ◽  
Preemptive Scheduling ◽  
Release Date ◽  
Enumeration Algorithm ◽  
Processing Times ◽  
Special Cases ◽  
Deadline Constraints ◽  
Special Case

Abstract It is known that the single machine preemptive scheduling problem of minimizing total completion time with release date and deadline constraints is NP- hard. Du and Leung solved some special cases by the generalized Baker's algorithm and the generalized Smith's algorithm in O(n2) time. In this paper we give an O(n2) algorithm for the special case where the processing times and deadlines are agreeable. Moreover, for the case where the processing times and deadlines are disagreeable, we present two properties which could enable us to reduce the range of the enumeration algorithm

Minimizing total completion time on uniform machines with deadline constraints

2006 ◽  
Vol 2 (1) ◽  
pp. 95-115 ◽  
Author(s):  
Teofilo F. Gonzalez ◽  
Joseph Y.-T. Leung ◽  
Michael Pinedo
Keyword(s):  
Completion Time ◽  
Total Completion Time ◽  
Uniform Machines ◽  
Deadline Constraints

Heuristics for Minimizing Total Completion Time on Single Machine with Release Time

2007 ◽  
Vol 18-19 ◽  
pp. 347-352 ◽  
Author(s):  
Elkanah Oyetunji ◽  
Ayodeji E. Oluleye
Keyword(s):  
Approximation Algorithm ◽  
Single Machine ◽  
Industrial Production ◽  
Completion Time ◽  
Service Sector ◽  
Total Completion Time ◽  
Release Time ◽  
Release Dates ◽  
The Best Approximation ◽  
Better Than

This paper focuses on the problem of scheduling n jobs with release dates on a single machine in order to minimize the total completion time. Since the problem has been characterized as strongly NP-hard, two heuristics (HR1 and AEO) were proposed for solving the problem in polynomial time. The heuristics were compared with the best approximation algorithm for this problem to date (Best-alpha). Experimental results show that AEO performed better than the Bestalpha algorithm (selected from the literature) when the number of jobs (n) exceeds 5. This observation should prove useful in the operational dispatch of jobs in industrial production settings as well as the service sector.

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