Hybrid heuristics for the permutation flow shop problem

M.G. Ravetti, F.G. Nakamura,, C.N. Meneses,  M. G. C. Resende, G.R. Mateus, and P. M. Pardalos

Submitted  to  European J. of Operational Research, 2006

ABSTRACT

The Flow Shop Problem (FSP) is known to be NP-hard when more than three machines are considered. Thus, for non-trivial size problem instances, heuristics are needed to find good orderings. We consider the permutation case of this problem. For this case, denoted by F|prmu|Cmax, the sequence of jobs has to remain the same at each machine. We propose and test two hybrid heuristics, combining elements from the standard Greedy Randomized Adaptive Search Procedure (GRASP), Iterated Local Search (ILS),  Path Relinking (PR) and Memetic Algorithm (MA). The results obtained are shown to be competitive with existing algorithms.



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