scholarly journals A Submodular Optimization Approach to Bicriteria Scheduling Problems with Controllable Processing Times on Parallel Machines

2013 ◽  
Vol 27 (1) ◽  
pp. 186-204 ◽  
Author(s):  
Akiyoshi Shioura ◽  
Natalia V. Shakhlevich ◽  
Vitaly A. Strusevich
2015 ◽  
Vol 3 (1) ◽  
pp. 68-76
Author(s):  
Guiqing Liu ◽  
Kai Li ◽  
Bayi Cheng

AbstractThis paper considers several parallel machine scheduling problems with controllable processing times, in which the goal is to minimize the makespan. Preemption is allowed. The processing times of the jobs can be compressed by some extra resources. Three resource use models are considered. If the jobs are released at the same time, the problems under all the three models can be solved in a polynomial time. The authors give the polynomial algorithm. When the jobs are not released at the same time, if all the resources are given at time zero, or the remaining resources in the front stages can be used to the next stages, the offline problems can be solved in a polynomial time, but the online problems have no optimal algorithm. If the jobs have different release dates, and the remaining resources in the front stages can not be used in the next stages, both the offline and online problems can be solved in a polynomial time.


2005 ◽  
Vol 8 (3) ◽  
pp. 233-253 ◽  
Author(s):  
Natalia V. Shakhlevich ◽  
Vitaly A. Strusevich

2021 ◽  
Vol 55 (2) ◽  
pp. 561-569
Author(s):  
Shan-Shan Lin

This note studies a unrelated parallel-machine scheduling problem with controllable processing times and job-dependent learning effects, where the objective function is to minimize the weighted sum of total completion time, total load, and total compression cost. We show that the problem can be solved in O(nm+2) time, where m and n are the numbers of machines and jobs. We also show how to apply the technique to several single-machine scheduling problems with total criteria.


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