Scheduling with Resource Allocation, Deteriorating Effect and Group Technology to Minimize Total Completion Time

Yan, Jia-Xuan; Ren, Nanqi; Bei, Hong-Bin; Han, Baohui; Wang, Ji‐Bo

doi:10.3390/math10162983

Cited by 8 publications

(2 citation statements)

References 22 publications

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“…The initial group sequence of the TS algorithm is decided in the non-decreasing order of s i , and the maximum number of iterations for the TS algorithm is set at 200Q (as in Yan et al [24], in general, the maximum number of iterations is 2000; here, it is set to 200Q).…”

Section: Phasementioning

confidence: 99%

Branch-and-Bound and Heuristic Algorithms for Group Scheduling with Due-Date Assignment and Resource Allocation

He,

Zhao,

et al. 2023

Mathematics

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Green scheduling that aims to enhance efficiency by optimizing resource allocation and job sequencing concurrently has gained growing academic attention. To tackle such problems with the consideration of scheduling and resource allocation, this paper considers a single-machine group scheduling problem with common/slack due-date assignment and a controllable processing time. The objective is to decide the optimized schedule of the group/job sequence, resource allocation, and due-date assignment. To solve the generalized case, this paper proves several optimal properties and presents a branch-and-bound algorithm and heuristic algorithms. Numerical experiments show that the branch-and-bound algorithm is efficient and the heuristic algorithm developed based on the analytical properties outruns the tabu search.

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Section: Phasementioning

confidence: 99%

Branch-and-Bound and Heuristic Algorithms for Group Scheduling with Due-Date Assignment and Resource Allocation

He,

Zhao,

et al. 2023

Mathematics

Self Cite

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show abstract

“…Liang et al [23] dealt with a single-machine resource allocation scheduling problem with deteriorating jobs and GT. Yan et al [24] studied a single-machine problem with resource allocation and deteriorating effect in group technology environment. Liu and Wang [25] and Wang and Liu [26] considered single-machine GT scheduling with resource allocation and due date assignment.…”

Section: Introductionmentioning

confidence: 99%

Scheduling with Group Technology, Resource Allocation, and Learning Effect Simultaneously

Li,

Lv,

et al. 2024

Mathematics

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This paper studies the single-machine group scheduling problem with convex resource allocation and learning effect. The number of jobs in each group is different, and the corresponding common due dates are also different, where the processing time of jobs follows a convex function of resource allocation. Under common due date assignment, the objective is to minimize the weighted sum of earliness, tardiness, common due date, resource consumption, and makespan. To solve the problem, we present the heuristic, simulated annealing, and branch-and-bound algorithms. Computational experiments indicate that the proposed algorithms are effective.

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Scheduling jobs with general linear deterioration to minimize total weighted number of late jobs

Yang

Geng

et al. 2023

Optim Lett

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Scheduling with Resource Allocation, Deteriorating Effect and Group Technology to Minimize Total Completion Time

Cited by 8 publications

References 22 publications

Branch-and-Bound and Heuristic Algorithms for Group Scheduling with Due-Date Assignment and Resource Allocation

Branch-and-Bound and Heuristic Algorithms for Group Scheduling with Due-Date Assignment and Resource Allocation

Scheduling with Group Technology, Resource Allocation, and Learning Effect Simultaneously

Scheduling jobs with general linear deterioration to minimize total weighted number of late jobs

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