Optimal due-date assignment problem with learning effect and resource-dependent processing times

Lu, Yuanyuan; Li, Gang; Wu, Yanpeng; Ji, Ping

doi:10.1007/s11590-012-0467-7

Cited by 64 publications

(25 citation statements)

References 33 publications

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“…Wang et al (2010) introduced the models p A jr (u j ) = p j r ρ − b j u j , and p A jr (u j ) = w j r ρ u j k , u j > 0, where w j is a positive parameter that represents the workload of the processing operation for job J j , u j is the amount of resource that can be allocated to job J j , and where k is a positive constant. Lu et al (2014), and Li et al (2015) introduced the…”

Section: Problem Descriptionmentioning

confidence: 99%

“…For several objective functions, they proposed polynomial time algorithms optimally. Lu et al (2014) considered single machine earliness-tardiness scheduling with resource allocation and learning effect. considered single machine common due window assignment scheduling with resource allocation and learning effect.…”

Section: Introductionmentioning

confidence: 99%

“…considered single machine common due window assignment scheduling with resource allocation and learning effect. Li et al (2015) studied the same model as Lu et al 2014 and combined it with due window assignment based on a common flow allowance. They solved both the linear and the convex function models under the specific objective by transforming to an assignment problem.…”

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: Problem Descriptionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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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“…Let p j be the actual processing time of job J j . As in Lu et al (2012), we consider the following models:…”

Section: Problem Formulationmentioning

confidence: 99%

Single-Machine Due-Window Assignment and Scheduling with Learning Effect and Resource-Dependent Processing Times

Wang

2014

Asia Pac. J. Oper. Res.

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We consider a single-machine common due-window assignment scheduling problem, in which the processing time of a job is a function of its position in a sequence and its resource allocation. The window location and size, along with the associated job schedule that minimizes a certain cost function, are to be determined. This function is made up of costs associated with the window location, window size, earliness, and tardiness. For two different processing time functions, we provide a polynomial time algorithm to find the optimal job sequence and resource allocation, respectively.

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“…learning effects, deteriorating jobs and resource-dependent processing times) can be found in Biskup (2008), Gawiejnowicz (2008), and Shabtay and Steiner (2007), respectively. More recently, Wang, Wang, and Wang (2010), Lu et al (2014), Wang (2014, 2015), considered sequencing and scheduling problems and models with learning effects and resource-dependent processing times. Wang (2013a, 2013b), Oron (2014), considered sequencing and scheduling problems and models with deteriorating jobs and resource-dependent processing times.…”

Section: Introductionmentioning

confidence: 99%

Due date assignment and convex resource allocation scheduling with variable job processing times

Sun¹,

Cui

Chen

et al. 2015

International Journal of Production Research

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This is a study of a earliness and tardiness sequencing and scheduling problem on a single machine. The processing time for job J j depends on its position in a sequence, its starting time, and its allocation of non-renewable resource. For three due date assignment methods i.e. the common due date, the slack due date and the unrestricted due date our goal is to find the optimal schedule, due dates, and resource allocations of jobs. We prove that three versions of the problem can be solved in polynomial time, respectively.

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Optimal due-date assignment problem with learning effect and resource-dependent processing times

Cited by 64 publications

References 33 publications

Resource constrained scheduling with general truncated job-dependent learning effect

Resource constrained scheduling with general truncated job-dependent learning effect

Single-Machine Due-Window Assignment and Scheduling with Learning Effect and Resource-Dependent Processing Times

Due date assignment and convex resource allocation scheduling with variable job processing times

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