Abstract:
The problem of scheduling jobs to minimize total weighted tardiness in flowshops,
with the possibility of evolving into hybrid flowshops in the future, is investigated in
this paper. As this research is guided by a real problem in industry, the flowshop
considered has considerable flexibility, which stimulated the development of an
innovative methodology for this research. Each stage of the flowshop currently has
one or several identical machines. However, the manufacturing company is planning
to introduce additional machines with different capabilities in different stages in the
near future. Thus, the algorithm proposed and developed for the problem is not only
capable of solving the current flow line configuration but also the potential new
configurations that may result in the future. A meta-heuristic search algorithm based
on Tabu search is developed to solve this NP-hard, industry-guided problem. Six
different initial solution finding mechanisms are proposed. A carefully planned
nested split-plot design is performed to test the significance of different factors and
their impact on the performance of the different algorithms. To the best of our
knowledge, this research is the first of its kind that attempts to solve an industry-guided
problem with the concern for future developments.
Description:
This is the author's peer-reviewed final manuscript, as accepted by the publisher. The published article is copyrighted by Elsevier and can be found at: http://www.journals.elsevier.com/expert-systems-with-applications/.
