What is it about?

In this article two multi-stage stochastic linear programming models were developed and applied to an aggregate production plan (APP) for a furniture manufacturing company located in the state of Hidalgo. Production capacity and demand are defined as random variables of the model. The main purpose of this research is to determine a feasible solution to the aggregate production plan in a reasonable computational time. The developed models were compared and analyzed.

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Why is it important?

Carrying out an aggregate plan is important in manufacturing industries, especially those where it is planned in periods of 3 to 18 months, or medium term. The production plan seeks to determine the optimal levels of production, hiring, layoffs, inventories, subcontracting, etc. The motivation for this work is to improve productivity, have efficient policies to manage its production and minimize production costs, developing models of aggregate production plans (APP) with uncertainty due to a real need: production capacity and demand, considering the service level. Additionally, a methodology to deal with problems using stochastic programming is proposed, although it was applied to the case of this APP.


Aggregate production plans play an important role in SMEs because they allow them to manage their resources and operations efficiently. This plays an important role in planning as it reduces the risk of SMEs disappearing, particularly in Mexico. Since many of the APPs occupy neither linear functions, a direction for future research is to make a model considering some non-linear functions, such as the inventory cost, also reformulate the problem, removing some restrictions for solving the problem in a more efficient way.

Eva Selene Hernández Gress
Instituto Tecnologico y de Estudios Superiores de Monterrey

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This page is a summary of: Production planning of a furniture manufacturing company with random demand and production capacity using stochastic programming, PLoS ONE, June 2021, PLOS,
DOI: 10.1371/journal.pone.0252801.
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