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Growing Science » International Journal of Industrial Engineering Computations » Incorporating batching decisions and operational constraints into the scheduling problem of multisite manufacturing environments

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International Journal of Industrial Engineering Computations

ISSN 1923-2934 (Online) - ISSN 1923-2926 (Print)
Quarterly Publication
Volume 12 Issue 3 pp. 345-364 , 2021

Incorporating batching decisions and operational constraints into the scheduling problem of multisite manufacturing environments Pages 345-364 Right click to download the paper Download PDF

Authors: Sergio Ackermann, Yanina Fumero, Jorge M. Montagna

DOI: 10.5267/j.ijiec.2021.1.002

Keywords: Multisite batch facilities, Batching, Scheduling, Operational policies, MILP model

Abstract: In multisite production environments, the appropriate management of production resources is an activity of fundamental relevance to optimally respond to market demands. In particular, each production facility can operate with different policies according to its objectives, prioritizing the quality and standardization of the product, customer service, or the overall efficiency of the system; goals which must be taken into account when planning the production of the entire complex. At the operational level, in order to achieve an efficient operation of the production system, the integrated problem of batching and scheduling must be solved over all facilities, instead of doing it for each plant separately, as has been usual so far. Then, this paper proposes a mixed-integer linear programming model for the multisite batching and scheduling problems, where different operational policies are considered for multiple batch plants. Through two examples, the impact of policies on the decision-making process is shown.

How to cite this paper
Ackermann, S., Fumero, Y & Montagna, J. (2021). Incorporating batching decisions and operational constraints into the scheduling problem of multisite manufacturing environments.International Journal of Industrial Engineering Computations , 12(3), 345-364.

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Journal: International Journal of Industrial Engineering Computations | Year: 2021 | Volume: 12 | Issue: 3 | Views: 652 | Reviews: 0

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