Batch scheduling of identical jobs with controllable processing times

In this paper, we study the problem of unrelated parallel machine scheduling with controllable processing times and deteriorating maintenance activity. The jobs are nonresumable. The processing time of each job is a linear function of the amount of a continuously divisible resource allocated to the job. During the planning horizon, there is at most one maintenance activity scheduled on each machine. Additionally, if the starting time of maintenance activity is delayed, the length of the maintenance activity required to perform will increase. Considering the total completion times of all jobs, the impact of maintenance activity in the form of the variation in machine load and the amounts of compression, we need to determine the job sequence on each machine, the location of maintenance activities and processing time compression of each job simultaneously. Accordingly, a polynomial time solution to the problem is provided.

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Linear programming relaxation algorithm for scheduling problem with controllable processing times

2009 ISECS International Colloquium on Computing, Communication, Control, and Management ◽

10.1109/cccm.2009.5268146 ◽

2009 ◽

Author(s):

Feng Zhang ◽

Lili Liu

Keyword(s):

Linear Programming ◽

Linear Programming Relaxation ◽

Controllable Processing Times ◽

Scheduling Problem ◽

Relaxation Algorithm ◽

Processing Times

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Multicriteria scheduling with controllable processing times, setup times, and learning, ageing and deterioration effects on a single machine

European J of Industrial Engineering ◽

10.1504/ejie.2016.078140 ◽

2016 ◽

Vol 10 (4) ◽

pp. 455 ◽

Cited By ~ 2

Author(s):

H.M. Soroush

Keyword(s):

Single Machine ◽

Setup Times ◽

Controllable Processing Times ◽

Processing Times ◽

Multicriteria Scheduling

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A STOCHASTIC BATCHING AND SCHEDULING PROBLEM

Probability in the Engineering and Informational Sciences ◽

10.1017/s0269964801154033 ◽

2001 ◽

Vol 15 (4) ◽

pp. 465-479 ◽

Cited By ~ 2

Author(s):

Ger Koole ◽

Rhonda Righter

Keyword(s):

Optimal Policy ◽

Semiconductor Manufacturing ◽

Processing Time ◽

Polynomial Time Algorithm ◽

Time Algorithm ◽

Flow Time ◽

Batch Scheduling ◽

Scheduling Problem ◽

Processing Times ◽

Deterministic Problem

We consider a batch scheduling problem in which the processing time of a batch of jobs equals the maximum of the processing times of all jobs in the batch. This is the case, for example, for burn-in operations in semiconductor manufacturing and other testing operations. Processing times are assumed to be random, and we consider minimizing the makespan and the flow time. The problem is much more difficult than the corresponding deterministic problem, and the optimal policy may have many counterintuitive properties. We prove various structural properties of the optimal policy and use these to develop a polynomial-time algorithm to compute the optimal policy.

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Efficient scheduling of a stochastic no-wait job shop with controllable processing times

Expert Systems with Applications ◽

10.1016/j.eswa.2020.113879 ◽

2020 ◽

Vol 162 ◽

pp. 113879

Author(s):

Alexander Aschauer ◽

Florian Roetzer ◽

Andreas Steinboeck ◽

Andreas Kugi

Keyword(s):

Job Shop ◽

Controllable Processing Times ◽

Processing Times ◽

No Wait

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Preemptive Scheduling with Controllable Processing Times on Parallel Machines

Journal of Systems Science and Information ◽

10.1515/jssi-2015-0068 ◽

2015 ◽

Vol 3 (1) ◽

pp. 68-76

Author(s):

Guiqing Liu ◽

Kai Li ◽

Bayi Cheng

Keyword(s):

Polynomial Time ◽

Resource Use ◽

Parallel Machines ◽

Optimal Algorithm ◽

Parallel Machine Scheduling ◽

Controllable Processing Times ◽

Scheduling Problems ◽

Processing Times ◽

Online Problems ◽

Machine Scheduling Problems

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.

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