Due-window assignment scheduling in the proportionate flow shop setting

Sun, Xinyu; Geng, Xin-Na; Liu, Tao

doi:10.1007/s10479-020-03653-1

Cited by 24 publications

(3 citation statements)

References 31 publications

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“…The manager assigns a certain amount of additional resources to the job to reduce and control the processing time of the artifact. Common limited resources are the financial budget, energy, fuel, or manpower (see Vixkson [8]; Shabtay and Kasoi [9]; Wang and Cheng [10]; Shabtay and Steiner [11]; Zhang et al [12]; Wang et al [13]). In production, due to machine failure or the processing time being too long, wear will inevitably occur and reduce the working rate, so maintenance activities can be carried out to reduce the job processing time (see Lee and Leon [14]; Wang and Wang [15]; Mosheiov and Sidney [16]; Bai et al [17]; Yin et al [18]; and Strusevich and Rustogi [19]).…”

Section: Introductionmentioning

confidence: 99%

Single-Machine Maintenance Activity Scheduling with Convex Resource Constraints and Learning Effects

et al. 2023

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In this paper, the single-machine scheduling problems under the common and slack due date assignments are studied, where the actual processing time of the job needs to consider some factors, such as convex resource allocation, maintenance activity, and learning effects. The goal of this study is to find the optimal sequence, maintenance activity location, resource allocation and common due date (flow allowance). The objective function is (1) to minimize the sum of scheduling cost (including the weighted sum of earliness, tardiness and common due date (flow allowance), where the weights are position-dependent weights) and resource consumption cost, and (2) to minimize the scheduling cost under the resource consumption cost which is bounded. We prove that these problems can be solved in polynomial time.

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Section: Introductionmentioning

confidence: 99%

Single-Machine Maintenance Activity Scheduling with Convex Resource Constraints and Learning Effects

et al. 2023

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“…e weight of the processing queue can be increased when the production efficiency of a certain period of time needs to be improved. For example, in the Didi taxi dispatching (a similar mode to Uber), orders placed in the morning offer a higher bonus to the driver, which can effectively improve customer satisfaction in these locations by better meeting the needs of customers going to work in the morning [30]." In this article, the results of Wang et al [21] are extended to the case of the due-window assignment with positiondependent weights (Wang et al [24], Wang et al [25], and Wang et al [31]).…”

Section: Introductionmentioning

confidence: 99%

Study on Single-Machine Group Scheduling with Due-Window Assignment and Position-Dependent Weights

Liu

Wang

et al. 2021

Mathematical Problems in Engineering

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This article considers a single-machine group scheduling problem with due-window assignment, where the jobs are classified into groups and the jobs in the same group must be processed in succession. The goal is to minimize the weighted sum of lateness and due-window assignment cost, where the weights depend on the position in which a job is scheduled (i.e., position-dependent weights). For the common, slack, and different due-window assignment methods, we prove that the problem can be solved polynomially, i.e., in O N log N time, where N is the number of jobs.

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“…Error results of the algorithms for T max . unrelated parallel machines (Sun et al[32]), extending the models to scheduling with variable processing times (Wang et al[33]), or considering the lateness/earliness objective functions (Liang et al[34], Wu et al[35], Wu et al[36], Sun et al[37], Lv et al[38], Wang et al[39]). …”

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confidence: 99%

Study on Scheduling Problems with Learning Effects and Past Sequence Delivery Times

He,

Zhao,

et al. 2023

Mathematics

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In this paper, we study a single-machine green scheduling problem with learning effects and past-sequence-dependent delivery times. The problem can be properly applied to tackle green manufacturing where production and delivery time are variable and highly subject to process-reengineering. Our goal is to determine the optimal sequence such that total weighted completion time and maximum tardiness are minimized. For the general case, we provide the analysis procedure of lower bound, and also propose the heuristic and branch-and-bound algorithms. Furthermore, computational experiments are conducted to demonstrate the effectiveness of our algorithms.

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Due-window assignment scheduling in the proportionate flow shop setting

Cited by 24 publications

References 31 publications

Single-Machine Maintenance Activity Scheduling with Convex Resource Constraints and Learning Effects

Single-Machine Maintenance Activity Scheduling with Convex Resource Constraints and Learning Effects

Study on Single-Machine Group Scheduling with Due-Window Assignment and Position-Dependent Weights

Study on Scheduling Problems with Learning Effects and Past Sequence Delivery Times

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