Two-machine flowshop scheduling with a truncated learning function to minimize the makespan

Cheng, T.C.E.; Wu, Chin-Chia; Chen, Juei-Chao; Wu, Chin‐Chia; Cheng, Shuenn‐Ren

doi:10.1016/j.ijpe.2012.03.027

Cited by 67 publications

(23 citation statements)

References 30 publications

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“…This subsection addresses the problem of finding the accepted job set and the optimal accepted job sequence to minimize the objective function given by (4) under model (2).…”

Section: The Problemmentioning

confidence: 99%

“…The corresponding scheduling problems have received considerable research attention. For reviews of scheduling problems involving the learning effect, the reader may refer to Cheng and Wang [1], Cheng et al [2,3], Janiak and Rudek [4][5][6], Kuo et al [7], Lee and Lai [8], Rudek [9], and Yin et al [10,11], while for reviews of research on scheduling with job deterioration, the reader may refer to Bachman et al [12,13], Inderfurth et al [14], Janiak and Kovalyov [15], Mazdeh et al [16], Yin et al [17][18][19], and Zhao and Tang [20]. For studies considering a mixed form of both learning and deterioration, we refer the reader to Cheng et al [21], Wang [22,23], Wang and Cheng [24], Wang et al [25][26][27], Yang and Kuo [28], and Yin and Xu [29].…”

Section: Introductionmentioning

confidence: 99%

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Single-Machine Scheduling with Job Rejection, Deteriorating Effects, and Deteriorating Maintenance Activities

Nian

Mao

2013

Mathematical Problems in Engineering

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This paper addresses the single-machine scheduling problems with simultaneous considerations of job rejection, deterioration effects, and deteriorating multimaintenance activities. A job is either rejected, in which case a rejection penalty has to be paid, or accepted and processed on the single machine. Three deterioration effect models are investigated, and it is assumed that each machine may be subject to several maintenance activities over the scheduling horizon, and the duration of the maintenance depends on its running time. Moreover, due to the restriction of the budget of maintenance, the upper bound of the total maintenance frequencies on the machine is assumed to be known in advance. The objective is to find jointly the optimal accepted job set, the optimal maintenance frequencies, the optimal maintenance positions, and the optimal accepted job sequence such that the cost function based on the total completion time and rejection penalty is minimized. It is shown that all the versions of the problem under study are polynomial time solutions.

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“…This subsection addresses the problem of finding the accepted job set and the optimal accepted job sequence to minimize the objective function given by (4) under model (2).…”

Section: The Problemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Single-Machine Scheduling with Job Rejection, Deteriorating Effects, and Deteriorating Maintenance Activities

Nian

Mao

2013

Mathematical Problems in Engineering

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“…An extensive survey of different scheduling models and problems involving jobs with learning effects can be found in Biskup (2008). Rudek (2011), Cheng et al (2013), and Liu and Feng (2014) considered the two-machine makespan minimization flow shop scheduling with learning effects, Rudek (2011) studied the case of a step 1136 J.-B. Wang et al / Intl.…”

Section: Introductionmentioning

confidence: 99%

“…Res. 26 (2019) [1135][1136][1137][1138][1139][1140][1141][1142][1143][1144][1145][1146][1147][1148][1149][1150][1151] learning curve, Cheng et al (2013) studied the case of a truncated learning function, and Liu and Feng (2014) studied the case of convex resource-dependent processing times and learning effect. Xu et al (2008), Wu and Lee (2009), Kuo et al (2012), Li et al (2013), Lee and Chung (2013), Sun et al (2013aSun et al ( , 2013b, Wang and Wang (2012), Wang et al (2013), Wang and Wang (2014), and Wang and Zhang (2015) considered the m-machine flow shop scheduling with learning effects.…”

Section: Introductionmentioning

confidence: 99%

Research on m‐machine flow shop scheduling with truncated learning effects

Wang

Liu

Wang

2016

Int Trans Operational Res

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The permutation flow shop problems with truncated exponential sum of logarithm processing times based and position‐based learning effects are considered in this study. The objective is to minimize makespan and total weighted completion time, respectively. Several heuristics and a branch‐and‐bound algorithm are proposed in this paper. The tight worst‐case bounds of some simple heuristics are also given. Numerical experiments are tested to evaluate the performance of the heuristics and branch‐and‐bound algorithm.

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“…For the latter, they show the problem is weakly NP-hard. For recent works with two-agent settings, the reader may refer to Cheng (2012), Cheng et al (2013), Elvikis and Kindt (2014), Mosheiov (2013, 2014), Yin et al (2012aYin et al ( , b, c, 2013a and Wu et al (2013Wu et al ( , 2014a, etc. For more other details with multiagent scheduling issues, the reader may refer to the book by Agnetis et al (2014).…”

Section: Introductionmentioning

confidence: 99%

A two-agent single-machine scheduling problem to minimize the total cost with release dates

Wang

Yin

et al. 2015

Soft Comput

Self Cite

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This paper considers a two-agent scheduling problem with arbitrary release dates on a single machine. The cost of the first agent is the maximum weighted completion time of its jobs while the cost of the second agent is the total weighted completion time of its jobs. The goal is to schedule the jobs such that the total cost of the two agents is minimized. The problem is known to be strongly NP-hard. Thus, as an alternative, a branch-and-bound algorithm incorporating several dominance properties and a lower bound is provided to derive the optimal solution and a largest-order-value method combined with proposed three initials is developed to derive the near-optimal solutions for the problem. Computational results are also presented to evaluate the performance of the proposed algorithms.

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Two-machine flowshop scheduling with a truncated learning function to minimize the makespan

Cited by 67 publications

References 30 publications

Single-Machine Scheduling with Job Rejection, Deteriorating Effects, and Deteriorating Maintenance Activities

Single-Machine Scheduling with Job Rejection, Deteriorating Effects, and Deteriorating Maintenance Activities

Research on m‐machine flow shop scheduling with truncated learning effects

A two-agent single-machine scheduling problem to minimize the total cost with release dates

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