Fertilizer application management under uncertainty using approximate dynamic programming

Research output: Contribution to journalArticlepeer-review

Abstract

Finding the right amount of fertilizer for the plants in different maturity levels is a dynamic and stochastic problem due to the uncertainties in the weather conditions and yields. Besides, two conflicting objectives of multiple stakeholders, maximizing the yield and minimizing the environmental impact should be considered together. This paper proposes a mathematical model based on stochastic dynamic programming to find the fertilization levels in a citrus orchard for a finite planning period. Due to the size of the problem, we develop an Approximate Dynamic Programming (ADP) algorithm to obtain the best policy. The data for the case study is collected through literature sources and from farmers in southern Turkey where the income from orchards are unstable and groundwater pollution is observed. We find that ADP performs better than static and dynamic heuristics in a wide range of parameters. Extensive sensitivity analysis indicates that if the penalty for the leaching is computed per acre of orchard, this may lead to excessive fertilizer use in large orchards. Finally, the increase in the standard deviation of rainfall due to the global warming is expected to cause up to 22% drop in the yield.

Original languageEnglish
Article number107624
JournalComputers and Industrial Engineering
Volume161
Early online date18 Aug 2021
DOIs
Publication statusE-pub ahead of print - 18 Aug 2021

Keywords

  • Dynamic programming
  • Environmental operations
  • Public policy
  • Stochastic methods
  • UNSDGs

ASJC Scopus subject areas

  • Computer Science(all)
  • Engineering(all)

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