A bounded-search iterated greedy algorithm for the distributed permutation flowshop scheduling problem

Victor Fernandez-Viagas and Jose M. Framinan

International Journal of Production Research, 2015, vol. 53, issue 4, 1111-1123

Abstract: As the interest of practitioners and researchers in scheduling in a multi-factory environment is growing, there is an increasing need to provide efficient algorithms for this type of decision problems, characterised by simultaneously addressing the assignment of jobs to different factories/workshops and their subsequent scheduling. Here we address the so-called distributed permutation flowshop scheduling problem, in which a set of jobs has to be scheduled over a number of identical factories, each one with its machines arranged as a flowshop. Several heuristics have been designed for this problem, although there is no direct comparison among them. In this paper, we propose a new heuristic which exploits the specific structure of the problem. The computational experience carried out on a well-known testbed shows that the proposed heuristic outperforms existing state-of-the-art heuristics, being able to obtain better upper bounds for more than one quarter of the problems in the testbed.

Date: 2015
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DOI: 10.1080/00207543.2014.948578

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