Directing the Search of Evolutionary and Neighbourhood-Search Optimisers for the Flowshop Sequencing Problem with an Idle-Time Heuristic (1997)
| Venue: | In The 1997 AISB Workshop on Evolutionary Computing |
| Citations: | 1 - 1 self |
BibTeX
@INPROCEEDINGS{Ross97directingthe,
author = {Peter Ross and Andrew Tuson},
title = {Directing the Search of Evolutionary and Neighbourhood-Search Optimisers for the Flowshop Sequencing Problem with an Idle-Time Heuristic},
booktitle = {In The 1997 AISB Workshop on Evolutionary Computing},
year = {1997}
}
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Abstract
. This paper presents a heuristic for directing the neighbourhood (mutation operator) of stochastic optimisers, such as evolutionary algorithms, so to improve performance for the flowshop sequencing problem. Based on idle time, the heuristic works on the assumption that jobs that have to wait a relatively long time between machines are in an unsuitable position in the schedule and should be moved. The results presented here show that the heuristic improves performance, especially for problems with a large number of jobs. In addition the effectiveness of the heuristic and search in general was found to depend upon the neighbourhood structure in a consistent fashion across optimisers. 1 Introduction One problem of interest in the artificial intelligence and operations research scheduling communities is the flowshop sequencing problem. The aim of this problem is, quite simply, to find a sequence of n jobs that minimises the makespan --- the time for all of the jobs to be proces...
