ABSTRACT THE decision-making process associated with the scheduling of burley tobacco harvesting operations was formulated as a multi-stage decision process, and solved using a procedure called dynamic programming. The solution of a stochastic dynamic programming model provides a set of optimal decision rules, that is, a strategy. When certain user-specified parameters are provided, the decision model provides information concerning the optimal date to start harvesting, the optimal number of hours to harvest on each day, the optimal date to introduce hired labor, and the optimal number of workers which should be hired. The solution of the dynamic programming model makes it possible to compute a timeliness cost which is defined as the amount of the expected total return which is lost because of delaying harvest initiation be-yond the optimal starting day. Thus, a decision-maker can consult tabulated strategy solutions in any situation during the harvesting season and make decisions with the aid of timeliness cost information.
[1]
Albert N. Halter,et al.
A multi-stage stochastic replacement decision model : application to replacement of dairy cows
,
1963
.
[2]
E. M. Low,et al.
DYNAMIC PROGRAMMING AND THE SELECTION OF REPLACEMENT POLICIES IN COMMERCIAL EGG PRODUCTION
,
1967
.
[3]
P. B. Coaker,et al.
Applied Dynamic Programming
,
1964
.
[4]
H. E. Heggestad,et al.
Burley Tobacco Quality, Yield and Chemical Composition as Affected by Time of Harvest
,
1953
.
[5]
R. M. Peart,et al.
Optimum Policies for Corn Harvesting
,
1971
.
[6]
R. M. Peart,et al.
Dynamic Programming Method of Air Allocation in a Grain Dryer
,
1967
.