Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

The Optimal Harvest Decisions for Natural and Artificial Maturation Mangoes Under Uncertain Demand, Yields, and Prices

Version 1 : Received: 1 July 2021 / Approved: 2 July 2021 / Online: 2 July 2021 (15:44:52 CEST)

A peer-reviewed article of this Preprint also exists.

Chen, S.-I.; Chen, W.-F. The Optimal Harvest Decisions for Natural and Artificial Maturation Mangoes under Uncertain Demand, Yields and Prices. Sustainability 2021, 13, 9660. Chen, S.-I.; Chen, W.-F. The Optimal Harvest Decisions for Natural and Artificial Maturation Mangoes under Uncertain Demand, Yields and Prices. Sustainability 2021, 13, 9660.

Abstract

This study focuses on the decisions of picking, inventory, ripening, delivering, and selling mangoes in a harvesting season. Demand, supply, and prices are uncertain, and their probability density functions are fitted based on actual trading data collected from the largest spot market in Taiwan. A stochastic programming model is formulated to minimize the expected cost under the considerations of labor, storage space, shelf life, and transportation restrictions. We implement the sample-average approximation to obtain a high-quality solution of the stochastic program. The analysis compares deterministic and stochastic solutions to assess the uncertain effect on the harvest decisions. Finally, the optimal harvest schedule of each mango type is suggested based on the stochastic program solution.

Keywords

fresh agricultural products; harvest schedule; stochastic programming; sample-average approximation

Subject

Engineering, Automotive Engineering

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