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Title: Shift scheduling in multi-item production lines: a case study of a mineral water bottling company
Authors: Sifaleras, Angelo
Karakalidis, Alexis
Nikolaidis, Yiannis
Type: Article
Subjects: FRASCATI::Natural sciences::Mathematics::Applied Mathematics
FRASCATI::Natural sciences::Computer and information sciences
Keywords: Combinatorial Optimization
Production Optimization
Mathematical Programming
Mixed-Integer Programming
Issue Date: 2022
Publisher: Taylor & Francis
Source: International Journal of Systems Science: Operations & Logistics
Volume: 9
Issue: 1
First Page: 75
Last Page: 86
Abstract: It is well-known that the use of quantitative methods and modern analytics by companies in competitive markets is of vital importance both for their efficiency and financial profit. This study presents a novel, mathematical production-planning model for a real-world production optimization problem of a company located in Northern Greece. The company produces non-alcoholic soft drinks and needs to continuously allocate its human resources in order to have the optimum profit. Therefore, the objective of the model is the minimization of the company's idle human-hours subject to the fulfillment of the demand of customers. As algebraic modeling languages are well-suited for prototyping and developing optimization models, this production planning, mathematical model is implemented in Python v3.7.3 and solved using Gurobi solver v9.0. Furthermore, we also describe the competitive advantages offered by our quantitative approach and the initial allocation plan by the company.
ISSN: 2330-2674
Other Identifiers: 10.1080/23302674.2020.1818144
Appears in Collections:Department of Applied Informatics

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