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

Sheng-I Chen*, Chen Wei-Fu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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 variety is suggested based on the stochastic program solution.
Original languageAmerican English
Pages (from-to)1-17
Number of pages17
JournalSustainability
Volume13
Issue number9960
DOIs
StateAccepted/In press - 27 Aug 2021

Keywords

  • Fresh agricultural products
  • Harvest schedule
  • Stochastic programming
  • Sample-average approximation

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