A possibilistic model for production planning with uncertain demand

This article proposes a possibilistic model of production planning problem of a manufacturing company using a fuzzy representation of uncertainties in demand. An extension of chance constrained to fuzzy environments, and triangular numbers are employed to represent the variability in customers' orders. The operators required to convert the fuzzy model into an equivalent robust crisp one (RCM) are presented in the article. Moreover, the confidence levels of chance constraints are set as variables so that they are determined by the model, reducing the subjectivity in the selection of their values. The production planning problem is solved as a case study, to show the performance of the model. The results obtained are compared to two different alternative models: a deterministic one (DM) and a fuzzy approach (FeM). [Received 20 May 2018; Revised 29 May 2019; Revised 6 December 2019; Accepted 6 January 2020]