Single machine scheduling with resource constraints: Equivalence to two-machine flow-shop scheduling for regular objectives

Kovalev, Sergey; Chalamon, Isabelle; Bécuwe, Audrey

doi:10.1080/01605682.2023.2244529

Cited by 6 publications

(1 citation statement)

References 14 publications

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“…The CPU time of the heuristic algorithm is shorter compared to SA, and the error can be within the reasonable range (maximum error bound <0.5%). Future research could explore group scheduling under linear resource consumption function or with deterioration effects (Huang [35], Liu et al [36], Sun et al [37], Lv et al [38], Wang et al [39], Zhang et al [40], and Oron [41]) or deal with problems under flow shop setting (Sun et al [42], and Kovalev et al [43]).…”

Section: Discussionmentioning

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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