Single-machine scheduling with learning effect and resource-dependent processing times

Wang, Dan; Wang, Mingzheng; Wang, Jibo

doi:10.1016/j.cie.2010.06.002

Cited by 68 publications

(32 citation statements)

References 37 publications

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“…Practical cases of the model can be very well seen in the manufacturing environment of airplane maintenance, assembly workshop, clothing, etc. This paper extends the results of Wang et al (2010 by considering a more general truncated job-dependent learning effect and resource-dependent processing times model at the same time, and the results given in Wang et al (2010) as a special case are included.…”

Section: Introductionmentioning

confidence: 94%

“…The phenomena of resource allocation and learning effects occurring simultaneously can be found in many real-life situations (see Wang et al 2010). However, under the uncontrolled learning effect, the actual processing time of a job will plummet to zero dramatically, hence the use of the truncated learning effect is to model the phenomenon that the learning of a human activity is limited.…”

Section: Introductionmentioning

confidence: 98%

“…Wang et al (2010) considered single machine scheduling model with resource allocation and learning effect. For several objective functions, they proposed exact polynomial time algorithms.…”

Section: Introductionmentioning

confidence: 99%

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Resource constrained scheduling with general truncated job-dependent learning effect

Liu

Wang

2015

J Comb Optim

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Scheduling with general truncated job-dependent learning effect and resource-dependent processing times is studied on a single machine. It is assumed that the job processing time is a function of the amount of resource allocated to the job, the general job-dependent learning effect and the job-dependent control parameter. For each version of the problem that differs in terms of the objective functions and the processing time functions, the optimal resource allocation is provided. Polynomial time algorithms are also developed to find the optimal schedule of several versions of the problem.

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Section: Introductionmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 98%

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Resource constrained scheduling with general truncated job-dependent learning effect

Liu

Wang

2015

J Comb Optim

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“…Wei et al [36] and Wang and Wang [29] considered single-machine scheduling with time-and-resource-dependent processing times. Wang et al [34], Hsu et al [10] and Wang [23] considered single-machine scheduling with learning effects. Eren [4] and Hsu et al [8] considered parallelmachine scheduling with learning effects.…”

Section: Introductionmentioning

confidence: 99%

Resource-dependent scheduling with deteriorating jobs and learning effects on unrelated parallel machine

Jin

et al. 2015

Neural Comput & Applic

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The focus of this paper is to analyze unrelated parallel-machine resource allocation scheduling problem with learning effect and deteriorating jobs. The goal is to find the optimal sequence of jobs and the optimal resource allocation separately for minimizing the cost function including the total load, the total completion time, the total absolute deviation of completion time and the total resource cost. We show that the problem is polynomial time solvable if the number of machines is a given constant.

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“…This problem, i.e. the single-machine scheduling problem with convex resource dependent processing times, has been widely studied in the literature [13][14][15][16][17][18][19][20][21] due to the wide applicability of the convex resource consumption function and its tness for many real problems [22]. However, almost all the existing studies on the problem consider only one resource allocation, and there are very few studies on multiple resources.…”

Section: Introductionmentioning

confidence: 99%

Single machine scheduling problem with convex multi-resource dependent processing times and job deadlines

Ziaee

2017

Scientia Iranica

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Abstract. In this paper, the single-machine scheduling problem with convex multiresource dependent processing times, subject to meeting job deadlines, is considered. The objective is to minimize the total cost, including the resource allocation costs and the xed costs. We assume that the actual processing time of each job (task) is a function of the amount of resources allocated. Therefore, the decision variables of the model are: (1) resources allocated to the jobs; (2) total consumed resources; (3) processing times of the jobs; (4) start/completion times of the jobs. We reformulate and solve the problem using a posynomial geometric programming model. In the proposed exact solution method based on the geometric programming, the original problem of any size is reduced to a two-variable unconstrainted optimization problem, which can be easily solved by a simple grid search.

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Single-machine scheduling with learning effect and resource-dependent processing times

Cited by 68 publications

References 37 publications

Resource constrained scheduling with general truncated job-dependent learning effect

Resource constrained scheduling with general truncated job-dependent learning effect

Resource-dependent scheduling with deteriorating jobs and learning effects on unrelated parallel machine

Single machine scheduling problem with convex multi-resource dependent processing times and job deadlines

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