Developing a Multi-Stage Production Planning and Scheduling Model for a Small-Size Food and Beverage Company

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Date

2021

Journal Title

Journal ISSN

Volume Title

Publisher

International Information and Engineering Technology Association

Open Access Color

BRONZE

Green Open Access

No

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Publicly Funded

No
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Average
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Average
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Average

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Abstract

A great deal of research has been undertaken in recent years related to facility capacity expansion and production planning problems under deterministic and stochastic constraints in the literature. However, only a small portion of this work directly addresses the issues faced by the food and beverage industry, especially in small-sized enterprises. In this study, a Mixed-Integer Linear Programming model (MILP) is developed for production planning and scheduling decisions for a small-size company producing syrup and jam products. The main constraint is that the multiple syrup and jam production lines in the model share the same limited-capacity module designed for inventory planning. To this end, the present model offers an efficient solution for executing a multi-product, multi-period production line by finding the most satisfactory strategy to match the right product with the useable capacity leading to profit maximization. The present approach is capable of coping with varying demands by offering a detailed costing procedure and implementing an effective inventory model. © 2021 Lavoisier. All rights reserved.

Description

Keywords

Mathematical modeling, MILP, Multi-period, Multi-product, Optimization in food and beverage production, Production planning, Production scheduling

Fields of Science

0211 other engineering and technologies, 02 engineering and technology

Citation

WoS Q

Scopus Q

Q3
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OpenCitations Citation Count
2

Source

Journal Europeen des Systemes Automatises

Volume

54

Issue

2

Start Page

273

End Page

281

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Citations

Scopus : 5

Captures

Mendeley Readers : 33

SCOPUS™ Citations

5

checked on Feb 14, 2026

Page Views

2

checked on Feb 14, 2026

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