WASET
	%0 Journal Article
	%A Danping Lin and  C.K.M. Lee
	%D 2012
	%J International Journal of Industrial and Manufacturing Engineering
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 64, 2012
	%T A Multi-Level GA Search with Application to the Resource-Constrained Re-Entrant Flow Shop Scheduling Problem
	%U https://publications.waset.org/pdf/10976
	%V 64
	%X Re-entrant scheduling is an important search problem
with many constraints in the flow shop. In the literature, a number of
approaches have been investigated from exact methods to
meta-heuristics. This paper presents a genetic algorithm that encodes
the problem as multi-level chromosomes to reflect the dependent
relationship of the re-entrant possibility and resource consumption.
The novel encoding way conserves the intact information of the data
and fastens the convergence to the near optimal solutions. To test the
effectiveness of the method, it has been applied to the
resource-constrained re-entrant flow shop scheduling problem.
Computational results show that the proposed GA performs better than
the simulated annealing algorithm in the measure of the makespan
	%P 788 - 792