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

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...

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Vydané v:International journal of production research Ročník 53; číslo 4; s. 1111 - 1123
Hlavní autori: Fernandez-Viagas, Victor, Framinan, Jose M.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: London Taylor & Francis 16.02.2015
Taylor & Francis LLC
Predmet:
distributed permutation flowshop
Factories
Greedy algorithms
Heuristic
heuristics
Industrial plants
iterated greedy algorithm
Job shops
Mathematical problems
Optimization algorithms
Permutations
Production scheduling
Scheduling
State of the art
Studies
Work environment
Workshops
ISSN:0020-7543, 1366-588X
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Shrnutí: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.
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ISSN:0020-7543
1366-588X
DOI:10.1080/00207543.2014.948578