Copyright © 2010 Debasis Das et al. This is an open access article distributed under the
Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Demand for a seasonal product persists for a fixed period of time. Normally
the “finite time horizon inventory control problems” are formulated for this type
of demands. In reality, it is difficult to predict the end of a season precisely. It is
thus represented as an uncertain variable and known as random planning horizon.
In this paper, we present a production-inventory model for deteriorating items in
an imprecise environment characterised by inflation and timed value of money and
considering a constant demand. It is assumed that the
time horizon of the business period is random in nature and follows exponential
distribution with a known mean. Here, we considered the resultant effect of inflation
and time value of money as both crisp and fuzzy. For crisp inflation effect, the
total expected profit from the planning horizon is maximized using genetic algorithm
(GA) to derive optimal decisions. This GA is developed using Roulette wheel
selection, arithmetic crossover, and random mutation. On the other hand when the
inflation effect is fuzzy, we can expect the profit to be fuzzy, too! As for the fuzzy
objective, the optimistic or pessimistic return of the expected total profit is obtained
using, respectively, a necessity or possibility measure of the fuzzy event. The GA we
have developed uses fuzzy simulation to maximize the optimistic/pessimistic return
in getting an optimal decision. We have provided some numerical examples and
some sensitivity analyses to illustrate the model.