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Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Solving the distributed two machine flow-shop scheduling problem using differential evolution. / Dempster, P.; Li, P.; Drake, J.H.
Advances in Swarm Intelligence: 8th International Conference, ICSI 2017, Fukuoka, Japan, July 27 – August 1, 2017, Proceedings, Part I. ed. / Ying Tan; Hideyuki Tagaki; Yuhui Shi. Cham : Springer, 2017. p. 449-457 (Lecture Notes in Computer Science; Vol. 10385).Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
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TY - GEN
T1 - Solving the distributed two machine flow-shop scheduling problem using differential evolution
AU - Dempster, P.
AU - Li, P.
AU - Drake, J.H.
N1 - The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-61824-1_49
PY - 2017/8/1
Y1 - 2017/8/1
N2 - Flow-shop scheduling covers a class of widely studied optimisation problem which focus on optimally sequencing a set of jobs to be processed on a set of machines according to a given set of constraints. Recently, greater research attention has been given to distributed variants of this problem. Here we concentrate on the distributed two machine flow-shop scheduling problem (DTMFSP), a special case of classic two machine flow-shop scheduling, with the overall goal of minimising makespan. We apply Differential Evolution to solve the DTMFSP, presenting new best-known results for some benchmark instances from the literature. A comparison to previous approaches from the literature based on the Harmony Search algorithm is also given.
AB - Flow-shop scheduling covers a class of widely studied optimisation problem which focus on optimally sequencing a set of jobs to be processed on a set of machines according to a given set of constraints. Recently, greater research attention has been given to distributed variants of this problem. Here we concentrate on the distributed two machine flow-shop scheduling problem (DTMFSP), a special case of classic two machine flow-shop scheduling, with the overall goal of minimising makespan. We apply Differential Evolution to solve the DTMFSP, presenting new best-known results for some benchmark instances from the literature. A comparison to previous approaches from the literature based on the Harmony Search algorithm is also given.
U2 - 10.1007/978-3-319-61824-1_49
DO - 10.1007/978-3-319-61824-1_49
M3 - Conference contribution/Paper
SN - 9783319618234
T3 - Lecture Notes in Computer Science
SP - 449
EP - 457
BT - Advances in Swarm Intelligence
A2 - Tan, Ying
A2 - Tagaki, Hideyuki
A2 - Shi, Yuhui
PB - Springer
CY - Cham
T2 - The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-319-61824-1_49
Y2 - 28 July 2017 through 1 August 2017
ER -