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Multi-job lot streaming to minimize the weighted completion time in a hybrid flow shop scheduling problem with work shift constraint

Nejati, M ; Sharif University of Technology

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  1. Type of Document: Article
  2. DOI: 10.1007/s00170-013-5265-6
  3. Abstract:
  4. Lot streaming means breaking a lot into sublots, where sublots may be transferred to a number of machines for the operations. Here, the multi-job lot streaming problem in a multistage hybrid flow shop having identical parallel machines at stages with work-in-process (WIP) jobs, work shifts constraint, and sequence-dependent setup times is studied. The aim is to minimize the sum of weighted completion times of jobs in each shift in order to furnish a better machine utilization for the following shifts. Our model in meeting the job demands appropriates job scheduling onmachines for processing, the sequence of operations on allocated machines, the size of the sublots in the work shifts, the work completion times in all the shifts, and the jobs in each stage as the WIP jobs. To solve the problem, a genetic algorithm (GA) and simulated annealing (SA) are proposed to compute the best scheduling for the hybrid flow shop problem. Numerical illustrations demonstrate the applicability of the proposed model and the effectiveness of the GA
  5. Keywords:
  6. Genetic algorithm ; Mixed-integer non-linear programming (MINLP) ; Simulated annealing ; Business machines ; Genetic algorithms ; Nonlinear programming ; Problem solving ; Scheduling ; Stream flow ; Hybrid flow shop ; Hybrid flow shop problem ; Hybrid flow shop scheduling ; Identical parallel machines ; Lot streaming ; Mixed-integer nonlinear programming ; Sequence-dependent setup time ; Weighted completion time
  7. Source: International Journal of Advanced Manufacturing Technology ; Vol. 70, Issue. 1-4 , January , 2014 , pp. 501-514 ; ISSN: 02683768
  8. URL: http://link.springer.com/article/10.1007%2Fs00170-013-5265-6