Wu, Xiuli, Shen, Xianli, Zhao, Ning, Wu, Shaomin (2020) An improved discrete pigeon-inspired optimisation algorithm for flexible job shop scheduling problem. International Journal of Bio-Inspired Computation, 16 (3). pp. 181-194. ISSN 1758-0366. E-ISSN 1758-0374. (doi:10.1504/IJBIC.2020.10033325) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided) (KAR id:84010)
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Official URL: http://dx.doi.org/10.1504/IJBIC.2020.10033325 |
Abstract
The pigeon-inspired optimisation (PIO) algorithm, which is a new promising optimisation algorithm, has successfully solved many continuous optimisation problems. In the literature, however, little research has been conducted on its application to the combinational optimisation problems. This paper therefore tries to fill in this gap and applies the PIO algorithm to solve the flexible job shop scheduling problem (FJSP), which is a typical combinational optimisation problem. It proposes an improved discrete PIO (IDPIO) algorithm to minimise the makespan of FJSP and develops methods to optimise the time to carry out the map and compass operator or the landmark operator with the PIO. The discrete map, compass operator, and the discrete landmark operator are developed respectively. The experiment results show that the IDPIO algorithm can solve the FJSP effectively and efficiently.
Item Type: | Article |
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DOI/Identification number: | 10.1504/IJBIC.2020.10033325 |
Uncontrolled keywords: | discrete pigeon-inspired optimisation algorithm; flexible job shop scheduling problem; discretisation; map and compass operator; landmark operator. |
Subjects: | H Social Sciences > HA Statistics > HA33 Management Science |
Divisions: | Divisions > Kent Business School - Division > Department of Analytics, Operations and Systems |
Depositing User: | Shaomin Wu |
Date Deposited: | 09 Nov 2020 20:10 UTC |
Last Modified: | 04 Mar 2024 16:42 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/84010 (The current URI for this page, for reference purposes) |
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