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

  title={Improvements for multi-objective flow shop scheduling by Pareto Iterated Local Search},
  author={Martin Josef Geiger},
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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Publications referenced by this paper.
Showing 1-10 of 24 references

Variable neighborhood search

European Journal of Operational Research • 2008

Handbook of Metaheuristics, volume 57 of International Series in Operations Research & Management Science

Fred Glover, Gary A. Kochenberger, editors

Design of multi-objective evolutionary algorithms: Application to the flow-shop scheduling problem

Matthieu Basseur, Franck Seynhaeve, El-ghazali Talbi
In Congress on Evolutionary Computation (CEC’2002), • 2002
View 2 Excerpts

Scheduling: Theory, Algorithms, and Systems. Prentice-Hall

Michael Pinedo
Upper Saddle River, NJ, • 2002
View 1 Excerpt

Wȩglarz. Scheduling Computer and Manufacturing Processes

J. B lażewicz, K. H. Ecker, E. Pesch, G. Schmidt
View 1 Excerpt

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