Stochastic Programming for Agricultural Planning

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Problems related to agriculture are, in essence, stochastic because of the uncertain nature of their parameters. The uncertainty caused by factors such as climatic conditions on yield impacts many systems arising in this sector. Uncertainty and imperfect information involved therein are challenging decision-making, as decision-makers are led to make decisions before observing the realization of the random factors.

Traditional approaches to deal with agricultural problems do not integrate risks and uncertainties involved therein, while it is relevant to efficient managerial decision-making to consider uncertainties and respond to opportunities and threats. Stochastic optimization has been a key to solving problems related to agriculture and enhancing productivity and efficiency in this field. It helps manage uncertainty and provides robust solutions. Stochastic optimization provides decision-makers with the ability to make optimal management decisions and helps to minimize the costs associated with decision-making under uncertainty.

This paper focuses on stochastic programming and covers some of the theoretical foundations. It also focuses on recent advances in agriculture as an area where stochastic programming is applicable.

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