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.
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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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