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Permutation flowshop manufacturing cell scheduling problems with deteriorating jobs and sequence dependent setup times under dominant machines

  • Shaojun Lu
  • Xinbao Liu
  • Jun Pei
  • Panos M. Pardalos
Original paper
  • 67 Downloads

Abstract

This paper investigates permutation flowshop manufacturing cell scheduling problems with deteriorating jobs and sequence dependent setup times under dominant machines. In the proposed models, we need to make joint decisions on part families sequencing and jobs sequencing within each family. To solve the makespan minimization problem, the structural properties of the optimal solutions are derived, based on which an optimization algorithm is developed. Then, we consider the total completion time minimization problem and propose a useful lemma for the optimal solutions. Finally, we discuss two special cases of the problem and propose optimization algorithms to solve them respectively.

Keywords

Scheduling Flowshop Part family Deteriorating jobs Sequence dependent setup times Dominant machines 

Notes

Acknowledgements

This work is supported by the National Natural Science Foundation of China (Nos. 71231004, 71601065, 71690235, 71501058, 71601060), and Innovative Research Groups of the National Natural Science Foundation of China (71521001), the Humanities and Social Sciences Foundation of the Chinese Ministry of Education (No. 15YJC630097), Anhui Province Natural Science Foundation (No. 1608085QG167), Base of Introducing Talents of Discipline to Universities for Optimization and Decision-making in the Manufacturing Process of Complex Product (111 project), Fundamental Research Funds for the Central Universities (JZ2018HGTA0222, JZ2018HGBZ0113). Panos M. Pardalos is partially supported by the project of Distinguished International Professor by the Chinese Ministry of Education (MS2014HFGY026).

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of ManagementHefei University of TechnologyHefeiChina
  2. 2.Department of Industrial and Systems Engineering, Center for Applied OptimizationUniversity of FloridaGainesvilleUSA
  3. 3.Key Laboratory of Process Optimization and Intelligent Decision-Making of Ministry of EducationHefeiChina

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