Improvements for multi-objective flow shop scheduling by Pareto Iterated Local Search

@article{Geiger2009ImprovementsFM,
  title={Improvements for multi-objective flow shop scheduling by Pareto Iterated Local Search},
  author={Martin Josef Geiger},
  journal={CoRR},
  year={2009},
  volume={abs/0907.2993}
}
The flow shop scheduling problem consists in the assignment of a set of jobs J = {J1, . . . , Jn}, each of which consists of a set of operations Jj = {Oj1, . . . , Ojoj} onto a set of machines M = {M1, . . . ,Mm} [5, 18]. Each operation Ojk is processed by at most one machine at a time, involving a non-negative processing time pjk. The result of the problem resolution is a schedule x, defining for each operation Ojk a starting time sjk on the corresponding machine. Several side constraints are… CONTINUE READING

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