NSGA-II for Parallel Machine Scheduling with Tardiness and Extra QoS Cost Considerations

Zheng, Feifeng; Jin, Kaiyuan

doi:10.1109/icsssm.2019.8887842

Cited by 1 publication

(1 citation statement)

References 11 publications

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“…The results showed that the proposed algorithm was efficient and powerful when dealing with the multi-objective FJSP that included energy consumption [33]. Regarding multi-objective PMSP, Zheng et al investigated the PMSP of matching orders and factories; the objectives included minimizing the total tardiness and the extra quality of service costs, using NSGA-II to efficiently solve large-scale instances [34]. Although the designed algorithm considers the eligibility constraint relationship between orders and machines of a factory, orders are independent and non-decomposable minimum job units, which cannot solve scenarios containing kitting requirements.…”

Section: Introductionmentioning

confidence: 99%

Multi-Objective Parallel Machine Scheduling with Eligibility Constraints for the Kitting of Metal Structural Parts

Zhu

et al. 2022

Machines

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This paper studied a class of coupling problems of material assignment, part nesting, kit delivery and parallel machine scheduling. The aim of this paper was to solve the scheduling problem of metal structural part processing and welding assembly with eligibility constraints. A two-stage mixed-integer programming model was constructed. The eligibility constraints took into account the material type of parts and nesting. The objectives were to minimize the makespan, maximize material utilization and minimize the kit delivery metrics (kitting time and numbers of earliness and tardiness of kits). A hierarchical optimization approach was proposed. The scheduling model was solved by using the Gurobi solver in the first stage, and the results were used to constrain the second stage. The second stage of the scheduling model was solved using an improved multi-objective genetic algorithm. Due to the strong coupling relationships among the sorting of parts, the sorting of each profile and the sorting of each material, a hybrid encoding and decoding mode was designed for part sorting with eligibility constraints. Finally, the proposed scheduling approach was applied to actual production cases. The data showed that when the number of components exceeded 300 (the number of parts was about 1500), the material utilization reached 95%. Choosing a suitable number of machines, machine utilization reached 90%. The results demonstrated the effectiveness of the proposed scheduling model and algorithm.

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Section: Introductionmentioning

confidence: 99%

Multi-Objective Parallel Machine Scheduling with Eligibility Constraints for the Kitting of Metal Structural Parts

Zhu

et al. 2022

Machines

View full text Add to dashboard Cite

show abstract

NSGA-II for Parallel Machine Scheduling with Tardiness and Extra QoS Cost Considerations

Cited by 1 publication

References 11 publications

Multi-Objective Parallel Machine Scheduling with Eligibility Constraints for the Kitting of Metal Structural Parts

Multi-Objective Parallel Machine Scheduling with Eligibility Constraints for the Kitting of Metal Structural Parts

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