An uncertain aggregate production planning model for vegetables

• Published in: 2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) pp. 1386 - 1395
• Main Authors: Pang, Na, Ning, Yufu
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.07.2017
• Subjects: aggregate production planning; Aggregates; Capacity planning; Hidden Markov models; Planning; uncertain programming; Uncertainty; uncertainty theory; vegetables
• DOI: 10.1109/FSKD.2017.8392968

Aggregate production planning is made for the future production and there might be many unpredictable disruptions in actual production, which makes the historical data become unreliable. Meantime, long lead-times, short sales cycle, fast updating speed and volatile markets of the perishable vegetables usually makes the demand, deterioration rate and other factors obtained on the basis of belief degree. So we use uncertainty theory to study the aggregate production planning problem for vegetables from the point of manufacturers. According to the characteristic of sensitivity to storage time and overproduction, we build an uncertain aggregate production planning model for vegetables based on the price discount affected by the freshness and the overproduction punishment subject to the penalty function under the capacity constraints. Moreover, the model with uncertain variables obeying linear uncertain distributions can be transformed into the crisp equivalent form, which can be solved by traditional methods. Finally, a numerical example is carried out to illustrate the effectiveness of the proposed model.