A Markov decision algorithm for optimal pest control through uniform catastrophes

Article Abstract:

A Markov decision algorithm for solving the stochastic growth of a pest population is developed. This involves the incorporation of uniform catastrophes and an optimality criterion involving minimizing the long-term average cost per unit time. The class of monotone policies introduces catastrophes if and only if population size is equivalent to or greater than a critical value x. The Markov decision algorithm is developed in the absence of a condition under which the never controlling policy is optimal.

Software, Algorithms, Pests, Control, Pest control

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Optimal control of a simple immigration-birth-death process through total catastrophes

Article Abstract:

A study was conducted on the optimal control of a single immigration-birth-death process through the introduction of total catastrophes. The minimization of long-term average cost per unit time was designated as the optimality criterion. A semi-Markov decision model with a finite set of decision epochs can be formulated if birth, death and catastrophe rates satisfy a given condition. Results showed that the optimal policy is of the control-limit type by the standard policy iteration algorithm.

Catastrophes (Mathematics)

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Optimal pest control through the introduction of a predator

Article Abstract:

A Markov decision model was developed for optimal pest control where a predator is introduced. The minimization of long-term average cost per unit time was designated as the optimality criterion. An optimal policy was determined which undertakes controlling action only when the pest population size equals or exceeds a critical value. The optimality of the policy to a broader class of all stationary policies was subsequently proved.

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