Scheduling the operations of a double-load crane in slab yards-accepted.pdf (442.66 kB)

Scheduling the operations of a double-load crane in slab yards

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journal contribution
posted on 14.06.2019, 08:13 by Guodong Zhao, Jiyin Liu, Yun Dong
This paper studies a double-load crane scheduling problem (DLCSP) in steel slab yards. A slab yard stores slabs in stacks. To prepare for use in production, some slabs need to be moved from one place to another. These movement tasks are performed by a double-load crane which can hold up to two slabs simultaneously. Given a set of tasks and possibly precedence relationship among them, the scheduling problem is to allocate the tasks to double-load operations and determine the schedule for the crane to perform the tasks so as to minimize the makespan. The problem is first formulated as a mixed integer linear programming (MILP) model with variables representing the order of tasks. Based on properties of the problem, it is then reformulated from a crane operation perspective. Computational experiments are carried out on practical data collected from a steel company. The results show that both models can solve practical sized problems optimally, with the second model being more efficient.

Funding

National Key Research and Development Program of China (2016YFB0901900), the Fund for Innovative Research Groups of the National Natural Science Foundation of China (71621061), the Major International Joint Research Project of the National Natural Science Foundation of China (71520107004), General fund of the National Natural Science Foundation of China (71472081), and the 111 Project (B16009).

History

School

  • Business and Economics

Department

  • Business

Published in

International Journal of Production Research

Volume

58

Issue

9

Pages

2647-2657

Citation

ZHAO, G., LIU, J. and DONG, Y., 2019. Scheduling the operations of a double-load crane in slab yards. International Journal of Production Research, 58(9), pp. 2647-2657.

Publisher

© Taylor & Francis

Version

AM (Accepted Manuscript)

Publisher statement

This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Production Research on 25 June 2019, available online: http://www.tandfonline.com/10.1080/00207543.2019.1629666.

Acceptance date

29/05/2019

Publication date

2019-06-25

Copyright date

2020

ISSN

0020-7543

eISSN

1366-588X

Language

en

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