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Continuous-time formulation and differential evolution algorithm for an integrated batching and scheduling problem in aluminium industry

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journal contribution
posted on 2020-06-08, 12:57 authored by Q Guo, L Tang, Jiyin LiuJiyin Liu, S Zhao
© 2020, © 2020 Informa UK Limited, trading as Taylor & Francis Group. This paper investigates an integrated batching and scheduling problem of electrolysis and caster in aluminium industry. The problem is to determine the assignment and scheduling of orders considering sequence-dependent setup times caused by technological and operational constraints of electrolysis cells, and determine the batching and scheduling of orders in the following casters. A novel unit-specific event-based continuous-time mixed integer linear programming model (MILP) is proposed to describe the problem. In this model, the event point is stage specific, and lower bounds are specified to tighten the model. A hybrid pointer-based differential evolution algorithm with new individual representation scheme is designed to solve the problem of industrial scale. An improved hybrid pointer-based mutation operator and a new point-cross crossover operator are proposed to enhance the performance of the algorithm. Computational experiments show that the proposed algorithm is more efficient when compared with CPLEX for medium and large size instances. Comparisons with the lower bound demonstrate that the algorithm is effective.

Funding

Fund for Innovative Research Groups of the National Natural Science Foundation of China (71621061)

National Natural Science Foundation of China (71602025)

Major International Joint Research Project of the National Natural Science Foundation of China (71520107004)

111 Project (B16009)

History

School

  • Business and Economics

Department

  • Business

Published in

International Journal of Production Research

Volume

59

Issue

10

Pages

3169-3184

Publisher

Taylor and Francis

Version

  • AM (Accepted Manuscript)

Rights holder

© Taylor and Francis

Publisher statement

This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Production Research on 06 Apr 2020, available online: https://doi.org/10.1080/00207543.2020.1747656

Acceptance date

2020-03-18

Publication date

2020-04-06

Copyright date

2021

ISSN

0020-7543

eISSN

1366-588X

Language

  • en

Depositor

Prof Jiyin Liu 2020

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