Single-Machine Scheduling with Learning Effects and Maintenance: A Methodological Note on Some Polynomial-Time Solvable Cases
Keyword(s):
This work addresses four single-machine scheduling problems (SMSPs) with learning effects and variable maintenance activity. The processing times of the jobs are simultaneously determined by a decreasing function of their corresponding scheduled positions and the sum of the processing times of the already processed jobs. Maintenance activity must start before a deadline and its duration increases with the starting time of the maintenance activity. This work proposes a polynomial-time algorithm for optimally solving two SMSPs to minimize the total completion time and the total tardiness with a common due date.
2013 ◽
Vol 787
◽
pp. 1020-1024
1983 ◽
Vol 2
(2)
◽
pp. 62-65
◽
2012 ◽
Vol 6
(4)
◽
pp. 441
◽
2014 ◽
Vol 624
◽
pp. 675-680
2016 ◽
Vol 40
(21-22)
◽
pp. 8862-8871
◽
2012 ◽
Vol 62
(1)
◽
pp. 271-275
◽
2009 ◽
Vol 1
(2)
◽
pp. 161-177
◽